1. cyber phisical systems - interdisciplinary vision

Prof. Dr. Ing. Ioan DUMITRACHEProf. Dr. Ing. Ioan DUMITRACHE

University Politehnica of BucharestUniversity Politehnica of Bucharest

The Faculty of Automatic Control The Faculty of Automatic Control and Computersand Computers

TIMISOARA 2012TIMISOARA 2012

1.1. Factors and Challenges Factors and Challenges

2.2. Evolution of Computers, Control and Evolution of Computers, Control and CommunicationsCommunications

1.1. Towards a new computing paradigmTowards a new computing paradigm

2.2. The Evolution of Control SystemsThe Evolution of Control Systems

3.3. From the C2 Paradigm to the C4 ParadigmFrom the C2 Paradigm to the C4 Paradigm

1.1. Computer for Control Computer for Control

2.2. Computer – Communication and Cognition for ControlComputer – Communication and Cognition for Control

4.4. Impact of ICT on Advanced and Intelligent Control Impact of ICT on Advanced and Intelligent Control SystemsSystems

SummarySummary

5.5. Some Challenges for Control TechnologiesSome Challenges for Control Technologies

6.6. New Generation of Control SystemsNew Generation of Control Systems

7.7. Intelligent Control SystemsIntelligent Control Systems

8.8. Cyber-Physical Systems Cyber-Physical Systems

9.9. Science and Technology Challenges Science and Technology Challenges

10.10. Trends in Systems Science and Scientific Trends in Systems Science and Scientific ChallengesChallenges

11.11. ConclusionConclusion

SummarySummary

Increasing of complexity of critical infrastructures Increasing of complexity of critical infrastructures which supports the orderly functioning of the society which supports the orderly functioning of the society and economy at large;and economy at large;

Networked ICT Systems (‘eNetworks) have pervaded Networked ICT Systems (‘eNetworks) have pervaded in all traditional infrastructures, rendering then in all traditional infrastructures, rendering then more intelligent but more vulnerable at the same more intelligent but more vulnerable at the same time;time;

Supply networks: transportation grids for electrical Supply networks: transportation grids for electrical power, oil and gas; water distribution networks, power, oil and gas; water distribution networks, transport/road tunnel systems; production flow transport/road tunnel systems; production flow supply chains; health care systems;supply chains; health care systems;

Cyber-networks: tele-control and SCADA networks, Cyber-networks: tele-control and SCADA networks, e-banking/finance networks, etc;e-banking/finance networks, etc;

1.1. Factors and ChallengesFactors and Challenges

Managerial/organizational networks: the human Managerial/organizational networks: the human resources supervise and/or utilize the services resources supervise and/or utilize the services delivered by the above systems;delivered by the above systems;

Integration of physical devices with distributed Integration of physical devices with distributed sensing and actuation, communications, storage and sensing and actuation, communications, storage and computation mechanics to power, control and operate computation mechanics to power, control and operate virtually any device, appliance system/infrastructure – virtually any device, appliance system/infrastructure – “ The internet of the future”;“ The internet of the future”;

Developing of the Wireless Sensor/Actuator Networks Developing of the Wireless Sensor/Actuator Networks (WSAN) – could become pervasive in the near future;(WSAN) – could become pervasive in the near future;

Increasing of complexity of systems and the diversity Increasing of complexity of systems and the diversity of the embedded devices working into large of the embedded devices working into large networks;networks;


Globalization and the sever requirements for the Globalization and the sever requirements for the efficiency and greener economy – A new vision about efficiency and greener economy – A new vision about processes, products, productivity, efficiency and processes, products, productivity, efficiency and security;security;

Better understanding of biological systemsBetter understanding of biological systems

““Nature has not done analytical design, it has Nature has not done analytical design, it has produced brilliant iterative design”produced brilliant iterative design”

How do we shift our thinking to do the same?How do we shift our thinking to do the same?


Control of complex infrastructures – new concept of Control of complex infrastructures – new concept of COMPLEX ADAPTIVE SYSTEMS (“CAS”) - COMPLEX ADAPTIVE SYSTEMS (“CAS”) - Populations of interacting agentsPopulations of interacting agents

Control problems are integrated in infrastructures Control problems are integrated in infrastructures enhancing quality, reliability and efficiency - enhancing quality, reliability and efficiency - HIDDEN TECHNOLOGYHIDDEN TECHNOLOGY

COMPLEXITY - INTERCONNECTED COMPLEXITY - INTERCONNECTED INFRASTRUCTURES – INTERDEPENDENCY – INFRASTRUCTURES – INTERDEPENDENCY – CONNECTED – AGENTS – CAS – AUTONOMOUS CONNECTED – AGENTS – CAS – AUTONOMOUS SYSTEMSYSTEM


2. Evolution of Computers, Control and 2. Evolution of Computers, Control and CommunicationsCommunications

Optical bandwidth grows faster than processing power;

Wireless networks technology;

Internet of things, web of things;

Intelligent communication channel – INTERNET.

Mainframe ComputingMainframe Computing (60’s – 70’s) (60’s – 70’s) Large computers to execute large data processing Large computers to execute large data processing

applications.applications.Desktop Computing and InternetDesktop Computing and Internet (80’s – 90’s) (80’s – 90’s)

One computer at every desk to do business/personal One computer at every desk to do business/personal activities.activities.

Ubiquitous computing(00’s)Ubiquitous computing(00’s) Numerous computing devices in every place/person; Numerous computing devices in every place/person; ““Invisible” part of the environment; Invisible” part of the environment; Millions for desktops vs. billion for embedded processors.Millions for desktops vs. billion for embedded processors.

Cyber Physical Systems (10’)Cyber Physical Systems (10’) The next computing revolution?;The next computing revolution?; The physical world becomes integrable with computer The physical world becomes integrable with computer

networks → “Internet of Things” → “Web of Things”;networks → “Internet of Things” → “Web of Things”; Large number of embedded devices interconnected directly to Large number of embedded devices interconnected directly to

the internet.the internet. Integration of computation, communication, control and Integration of computation, communication, control and

physical process → (IC3PP)physical process → (IC3PP)

2.1 Towards a new computing 2.1 Towards a new computing paradigm paradigm

Empirical Control (time keeping with water closes)Empirical Control (time keeping with water closes)The industrial revolution (the problems of speed The industrial revolution (the problems of speed

control of the steam-machine)control of the steam-machine)The stability theory – ODE stabilityThe stability theory – ODE stability

I) “I) “Classical ControlClassical Control” ~(1900-1955)” ~(1900-1955)Formal recognition of feedback conceptFormal recognition of feedback conceptTransfer functions and Fourier TransformsTransfer functions and Fourier TransformsNyquist stability criteriaNyquist stability criteriaPID controllers PID controllers Graphical design tools-frequency based modelGraphical design tools-frequency based model

2.2 The Evolution of Control Systems2.2 The Evolution of Control Systems

II) “II) “Modern Control”Modern Control” ~ (1955-2000) ~ (1955-2000) Modern systems theory – state representationModern systems theory – state representation Digital computer in the loop/distributed control Digital computer in the loop/distributed control Hybrid systemsHybrid systems C2 → C3 → C4C2 → C3 → C4 Real progress in complexity designReal progress in complexity design LQ, LQGLQ, LQG Adaptive and optimal controlAdaptive and optimal control Robust control, H2/H∞ techniquesRobust control, H2/H∞ techniques Theory of nonlinear systems Theory of nonlinear systems LMI design LMI design MPCMPC

III) III) “Advanced and Intelligent” Control“Advanced and Intelligent” Control


Adaptive Control TheoryAdaptive Control Theory

Multi-model Adaptive ControlMulti-model Adaptive Control

PL A NT

C O N TR O L L E R S

w

yu

y~

AD AP TIVEM E C H AN ISM S

A -p r ior i k now le d g eI


Integration of systems; Integration of systems;

Integration of multiple technologies (engineering, Integration of multiple technologies (engineering, IT, Biology, etc…);IT, Biology, etc…);

Embedded systems;Embedded systems;

Brain behavior/cellular intelligenceBrain behavior/cellular intelligence ; ;More understanding of biological systems:More understanding of biological systems:

Biological systems can be viewed as interacting Biological systems can be viewed as interacting networks of genes, proteins and biochemical reactions, networks of genes, proteins and biochemical reactions, together with the external environmenttogether with the external environment


C2 – Control and Computing

New quality requirements and new challenges for control systems

intelligent control of complex distributed systems with moving and cooperating objects →intelligent space

Large real-time distributed networks → better understanding of dynamical behavior, the internal structures and design aspects of design and implementation → better knowledge and higher intelligence

3. From the C2 Paradigm to the C4 Paradigm

CC22 – Control and Computing : – Control and Computing :

CC33 – Control, Computing, and – Control, Computing, and

Communications :Communications :

C O N T R O L C O M P UT IN G

C O M M U NIC A T IO N S

F e e d b ac k ,F e e d -fo rw ard S tab ility ,O D E , P D E , M o d e rate

C o m p le x ity,O p tim izatio n ,

R o b u s tn e s s , F D I , . . .

L o g ic , L a n g u a g e s , D ES ,H ig h C o m ple x ity ,

A bs tra ct io n , A g e n ts , . . .

C O N T R O L C O M P U T IN G


Complexity of processesComplexity of processes distributed real-time control distributed real-time control

architecturesarchitectures

Global Enterprise ControlGlobal Enterprise Control

E X E C U TIV

C O O R D IN ATIO N

O R G AN IZATIO N AL

Str ate g i c , E nte r pr i s e Sys te m , G l o bal

Tac t i c al , M anufac tur i ng Sys te m

O pe r at i o nal , P r o c e s s C o ntr o l


Telecommunication-based control systems

Methods of remote and distributed control, remote

sensor data acquisition, tele-presence, tele-

operation, tele-maintenance, tele-diagnosis, tele-

education → facilitates the emergence and

development of a new class of control systems

which incorporate all aspects of intelligent

communication

Computer, Communication for ControlComputer, Communication for Control

CC33 Paradigm Paradigm

3.1 Computer for Control Computer-based Control

Integration of intelligent methodologies like : Fuzzy techniques;uzzy techniques; Neural networks;Neural networks; Evolutionary;Evolutionary; Cognitive techniquesCognitive techniques

In solving the problems of control systems : identification, modeling, decision making, identification, modeling, decision making, optimization, adaptation, and learningoptimization, adaptation, and learning → new attributes of Advanced Control SystemsAdvanced Control Systems are developed


New generation of control systems also includes

cognitive aspects from biology (living creatures)

Computers, Communications, Cognition, and Computers, Communications, Cognition, and

ControlControl play equal complementary roles in

addressing real-life problems, from small-scale

devices to large-scale industrial processes and

non-technical applications

CC44 Paradigm Paradigm


New advances in computers, communications and

cognitive sciences creates a new vision about

Advanced Control Systems, integrating some

attributes of intelligence : Perception;Perception; Planning;Planning; Learning;Learning; Communication;Communication; Reasoning.Reasoning.

Information and knowledge in actionInformation and knowledge in action


E m p iric alu n til th e en d o fth e 1 8 th c en tu r y

C las s ic al C o n tro l

1 9 0 0 - 1 9 5 5

M o de rn C o n tro l withcla s s ica l a rch it e ctu re s

1 9 5 5 - 1 9 9 0

C o m p u te r, C o m m u n ic atio n ,C o g n itio n fo r C o n tro l

(C 4 )A .I .C .S .

Hy b r id T eh c n iq u es

Hier ar c h ic a l an dHeter ar c h ic a l Arc h itec tu r es

S I S O s y s te m sL TIG ra ph ica l

M I M O s y s te m sNo n lin e a rA da pt iv e /O pt im a lS to ch a s t ic C o n tro lPre dict iv e C o n tro l

Ne w co n tro l th e o ry

Th e Th e o ry o fC o g n it iv e , R e a l-Tim eC o n tro l S y s te m s

2000


4. Impact of Information and Communication 4. Impact of Information and Communication Technology on Advanced and Intelligent Control Technology on Advanced and Intelligent Control

Systems (AICS)Systems (AICS) Convergence of Communications, Computing and Control Discrete Events and Hybrid Control;

Robust design and robust decision making will be based on stochastic techniques and randomization approaches;

New smart nanosensors and nanoactuators will continue to fertilize new control applications (medicine, biology, crystallography, optical communications, nanotechnology, etc);

New theories will be developed to handle complex and stochastic systems design very large distributed control systems and new effective real-time optimal algorithms for more complex sensing and signal processing.

Distributed Hybrid Control Systems very large model uncertainties a new vision on control theory and applications;

New quality requirements and new challenges for control systems;

Intelligent control of complex distributed systems with moving and cooperating objects intelligent space;

Large real-time distributed networks better understanding of dynamical behavior, the internal structures and design aspects of design and implementation better knowledge and higher intelligence.

4. Impact of Information and Communication 4. Impact of Information and Communication Technology on Advanced and Intelligent Control Technology on Advanced and Intelligent Control

Systems (AICS)Systems (AICS)

5. Some Challenges for Control 5. Some Challenges for Control TechnologiesTechnologies

New generation of controllers “SOFTWARE-“SOFTWARE-

INTENSIVE CONTROLLERS”INTENSIVE CONTROLLERS” embedded, fault-

tolerant, distributed, intelligent, integrated, open,

and heterogeneous;

Large distributed controllers are being developed as

communities of interacting intelligent agents;

Design shift from resource limitation to resource

adequacy, rendering more understandable solutions

possible.

Software-intensive distributed embedded controllers

are structured as dynamic collections of autonomous

real-time agents interacting with each other;

Solution inspired from biology and natural evolution

such as evolutionary algorithms, self-organized evolutionary algorithms, self-organized

neural networks, and immune systemsneural networks, and immune systems → NATURAL NATURAL

COMPUTATION;COMPUTATION;

Design and application of instruments and control

schemes for tele-monitoring, tele-presence, and tele-

control.

5. Some Challenges for Control 5. Some Challenges for Control TechnologiesTechnologies

Mathematical models must be integrated in large models with linguistic and symbolic representations where the knowledge and learning capability are connected to a perception and data acquisition system;

New methodologies like: fuzzy logicfuzzy logic, neural neural networksnetworks, KBKB, evolutionaryevolutionary and agent-based agent-based techniquestechniques are used to create complex models for complex processes and infrastructures:

Physical-based models;Nodal analysis models;Agent-based models;Stocks-and-flows models.

6. New Generation of Control Systems6. New Generation of Control Systems

Complex DEDSDEDS and HYBRIDHYBRID systems are included

into a large infrastructure;

The conventional mathematical methodologies that

underpin today’s modeling, simulation and control

paradigms are unable to handle the complexity and

interconnectedness of critical infrastructure such as

ENERGYENERGY, TELECOMMUNICATIONTELECOMMUNICATION,

TRANSPORTATIONTRANSPORTATION, and FINANCIAL.FINANCIAL.


NEWNEW CONCEPTS, NEW TECHNOLOGIES, NEW CONCEPTS, NEW TECHNOLOGIES, NEW

VISION on CONTROL and AUTOMATION of VISION on CONTROL and AUTOMATION of

COMPLEX SYSTEMSCOMPLEX SYSTEMS

New developments in the technology of sensors

and actuators:

new control application fields (Medicine, Biology,

Optical Communications and Nanotechnology)

new efforts for modeling, analysis, and design


Design of very large distributed control systemsDesign of very large distributed control systems

new theories will be developed to handle highly

complex systems, coordination of large numbers of

autonomous agents, to control hybrid and stochastic

systems with very large model uncertainties

Control over networks Control over networks will become an even more

important application area

embedded digital devices that interact with the

surrounding world via sensors and actuators, over a

widely distributed area linked by communication

networks (manufacturing plants, aircraft and traffic

control)



Design of distributed hybrid control systemsDesign of distributed hybrid control systems

new challenges for systems theory, modeling and

control of complexity

Specific technologies Specific technologies and complex systems complex systems will set new

quality requirements and new challenges for control

systems

multiagent distributed communication systems, mass

production in the automotive industry, in consumers’

electronics, in microelectronics, control in environmental

protection technologies, control of production in

renewable energy resources, etc.


Intelligent control of complex distributed systems Intelligent control of complex distributed systems

with moving and cooperating objects

intelligent space with ubiquitous sensory

intelligence

Cooperation between human and intelligent

robots (agents) into Intelligent Space

DIND – Distributed Intelligent Networked DIND – Distributed Intelligent Networked

DevicesDevices


DIND – Distributed Intelligent Networked DevicesDIND – Distributed Intelligent Networked Devices

S&A

S&A

S&AS

&A

S&A

A G 1

A G 2 A G 3

A G 4

A G n

D I N D

D I N D

D I N D

D I N D

D I N D

HB

S PA C E

C O O PER A TI O N NETW O R K


A key issue in control engineering is its application key issue in control engineering is its application

to highly complex systems :to highly complex systems :

the coupling of complicated and large

heterogeneous systems where different

disciplines are involved and different types of

information are available or have to be uncovered

or to be discovered


New approaches in control engineeringNew approaches in control engineering

““INFORMATION PROCESSING for ACTION”INFORMATION PROCESSING for ACTION”

Control, computers, communication and cognition play equal roles in addressing real-life problems from very small-scale devices to very large-scale industrial processes and non-technical applications

The C2 paradigmC2 paradigm of “Computers for Control”“Computers for Control” is shifting towards the C4 paradigmC4 paradigm of “Computers, “Computers, Communication, and Cognition for Control” Communication, and Cognition for Control”

integrated perspective on the role computers and control play in each field


Use of Open Market TechnologiesUse of Open Market Technologies

◦ from static information processingstatic information processing systems towards

dynamic information systemsdynamic information systems local component intelligence is increasing and large distributed controllers are being developed as communities of interacting intelligent agents

◦ standardizationstandardization and use of use of open-market technologiesopen-market technologies are current requirements in many control systems (new languages and platforms like Java, C# and CORBA are promising enhancements of ease and portability)

◦ development of generic tools, independent of the application domain the main drivers in control theory



◦ design support toolsdesign support tools need to be developed that automatically generate alternative solutions (models, controllers) to the problems

◦ dynamic reconfiguration of control strategies, software and hardware reconfiguration self-self-

organizing controllersorganizing controllers (using evolutionary programming, for instance)

◦ increase in the level of redundancy at all levels of hardware and software including sensors and actuators

◦ new design philosophy from resource limitation to resource adequacy rendering more understandable solutions possible



◦ Software-intuitive distributed embedded Software-intuitive distributed embedded

controllerscontrollers are structured as dynamic collections of autonomous real-time agents interacting with each other

◦ Control of communication networks real challenge for control theory and engineering, distributed control concepts including control with variable time delays

◦ Design and application of instruments and control schemes for telemonitoring, telepresence and telecontrol

7. Intelligent Control Systems7. Intelligent Control Systems

The joint functioning of several operators :The joint functioning of several operators :

◦ GROUPING

◦ FOCUSING OF ATTENTION

◦ SEARCHING

◦ FORMATION OF COMBINATIONS


Multiresolutional systems of knowledge (1)Multiresolutional systems of knowledge (1)

◦ NEUROSCIENCE

anatomical, physiological and chemical basis of behavior (Neuroanatomy, Neurophysiology, Neuropharmacology)

◦ BEHAVIORAL PSYCHOLOGY

added information about mental development, emotions and behavior

◦ LEARNING AUTOMATA and NEURAL NETS

brain modeling

7. Intelligent Control Systems7. Intelligent Control Systems Multiresolutional systems of knowledge (2)Multiresolutional systems of knowledge (2)

◦ COMPUTER SCIENCE and ARTIFICIAL INTELLIGENCE nature of language and image understanding rule-based reasoning, planning and problem

solving

◦ ROBOTICS and AUTONOMOUS NAVIGATION

advances in real-time sensory processing, world modeling, navigation, trajectory generation and obstacle avoidance

◦ GAME THEORY and OPERATION RESEARCH

methods for decision making in an uncertain environment


Multiresolutional systems of knowledge (3)Multiresolutional systems of knowledge (3)

◦ AUTOMATED MANUFACTURING and PROCESS CONTROL

has produced intelligent hierarchical controls, distributed databases, network

communications, multiprocessor-operating systems

◦ MODERN CONTROL THEORY

has developed precise understanding of stability, adaptability, and controllability under various conditions of feedback and noise

INTELLIGENCE (1)INTELLIGENCE (1)

◦ is a phenomenon that emerges as a result of the integration of knowledge and feedback into a

sensory-interactive, goal-directed, control systemsensory-interactive, goal-directed, control system that can make plans and generate effective, purposeful actions directed towards achieving them (ALBUS)

◦ a behavioral strategy that gives each individual a means of maximizing the likelihood of propagation its own genes


● INTELLIGENCE (2)INTELLIGENCE (2)

◦ is the integration of perception, reasoning, emotion and behavior in a sensing, perceiving, knowing, caring, planning and acting system that can succeed in achieving its goal in the world

◦ is the ability of a system to act appropriately in an uncertain environment, where appropriate action is that which increases the probability of success, and success is the achievement of behavioral sub-goals that support the system’s ultimate goal


● INTELLIGENCE (3)INTELLIGENCE (3)

◦ a computational phenomenon that emerges from the joint functioning of a closed loop with four fundamental processes

BEHAVIOR GENERATION (BG)BEHAVIOR GENERATION (BG)

WORLD MODELING (WM)WORLD MODELING (WM)

SENSORY PROCESSING (SP)SENSORY PROCESSING (SP)

VALUE JUDGMENT (VJ)VALUE JUDGMENT (VJ)


● DEGREES (LEVELS) of INTELLIGENCE DEGREES (LEVELS) of INTELLIGENCE

◦ the computational power of the system’s brain (or computer)

◦ the sophistication of algorithms the system uses for

Sensory ProcessingSensory Processing (SP), World ModelingWorld Modeling (WM),

Behavior GenerationBehavior Generation (BG), Value JudgmentValue Judgment (VJ),

Global CommunicationsGlobal Communications (GC)

◦ the information and value the system has stored in its memory

◦ the sophistication of the processes of the system’s functioning


● SENSORY PROCESSING SENSORY PROCESSING functions: functions:

◦ focus attention

◦ detect and group features

◦ compute attributes

◦ compare observations with expectations

◦ recognize objects and events

◦ analyze situations


● WORLD MODELING WORLD MODELING functions: functions:

◦ construct and maintain an internal representation of entities, events, relationships, and situations

◦ generate predictions, expectations, beliefs, and estimates of the probable results of future actions

● VALUE JUDGMENT VALUE JUDGMENT functions: functions:

◦ compute the cost, benefit, risk, and expected payoff of plans

◦ assign values to objects, events and situations

◦ decide what is important or trivial, what is rewarding or punishing, and what degree of confidence to assign to entries in the world model


● BEHAVIOR GENERATION BEHAVIOR GENERATION functions: functions:

◦ select goals

◦ decompose tasks

◦ generate plans

◦ coordinate activity

◦ control action

● All processes are linked together through a computational feedback control loop

● Interaction between top-down goals and bottom-up sensory feedback results in the phenomena known as intelligenceintelligence


● ELEMENTARY LOOP FUNCTIONING (ELF) (1)ELEMENTARY LOOP FUNCTIONING (ELF) (1)

◦ a primitive agent

WORLDMODEL

PERCEPTIONBEHAVIOR

GENERATION

SENSORS ACTUATIONENVIRONMENT

WORLDMODEL

PERCEPTIONBEHAVIOR

GENERATION

SENSORS ACTUATIONENVIRONMENT



◦ These computational loops from sensing to acting, from world modeling to sensory processing and from behavior generation to world modeling to value judgment and back are repeated many times within an intelligent system at many different levels



(S P - W M - B G )(E L F )1

S - W - A(E L F )2

1

2

ELF ELF ((EElementary lementary LLoop of oop of FFunctioning)unctioning)

P – perceptionK – knowledge base (WM)DM – decision makingA – actionW – real worldS – sensors

G – F – S Generalization, Focusing attention and

Search

(ELF)1 ↔ (ELF)2

(P → K → DM) → A(A → W → S) → P


● SENSING (1)SENSING (1)

◦ Developing tasks

◦ Sampling generation

◦ Sampling integration

◦ Sampling Coordination

● Usually several consecutive stages of generalizationgeneralization (bottom-up) and instantiationinstantiation (top-down) precede the use of a representation system in order to obtain a satisfactory control over its computational complexity

● The complexity of the representation will be dealt with by using GFSGFS for bottom-up generalizationbottom-up generalization and GFSGFS-1-1 for top-down instantiationtop-down instantiation


● SENSING (2)SENSING (2)

◦ At each level, feedback control loops have a

characteristic bandwidth and latency;

◦ This model of a multiresolutional hierarchy of

computational loops yields deep insight into the

phenomena of behavior, perception, cognition,

emotion, problem solving, and learning.


● Properties of an INTELLIGENT SYSTEMProperties of an INTELLIGENT SYSTEM

◦ recognize and make sense of a scene

◦ understand a sentence

◦ construct a correct response from the perceived situation

◦ form a sentence that is comprehensible and carrying a meaning of the selected response

◦ represent a situation internally

◦ perform tasks that require the discovery of relevant knowledge


● E.g. of an INTELLIGENT SYSTEM E.g. of an INTELLIGENT SYSTEM Intelligent Intelligent

RobotRobot

◦ a complete architecture of an intelligent robot generally includes four mechanisms : Moving Moving

mechanismmechanism, Manipulation mechanismManipulation mechanism,

PerceptionPerception, Central computer Central computer

◦ the operational aim of an intelligent robot is

autonomously performing anthropomorphic autonomously performing anthropomorphic

taskstasks in abominable environments and under the condition that temporal, spatial and capability constraints should not be violated


The action & perceptionaction & perception components at various levels of ICS for intelligent robots

Action component Perception component

Level 0Robot mechanism, moving

mechanism

Sensors of the body perceptions (force, displacement, velocity,

acceleration etc.)

Level 1Servo control of physical variable, outputs are current/volt signal to

actuator motors

Raw description of the world and its acquisition (estimation

learning)

Level 2Motion planner and strategies for the organization of the adjacent

lower level, trajectory generation

Geometrical and topological description of the world and its acquisition (learning, feature

abstraction etc.)

Level 3

Action sequence planner and strategies for the organization of the adjacent lower level, outputs are linguistically symbolic action

sequences

Linguistically symbolic description of the world and its acquisition (pattern recognition,

event detection etc.)


Strategic Level• Optimizing Performance monitoring• Planning Goal generation• Decision and learning

Coordination Level• Supervisor Learning• Decision making Planning• Fault diagnosis

Execution Level Control algorithms Estimation FDI algorithms Adaptation

SENSORS ACTIONS

ENVIRONMENT/ROBOTS

Strategic Level• Optimizing Performance monitoring• Planning Goal generation• Decision and learning

Coordination Level• Supervisor Learning• Decision making Planning• Fault diagnosis

Execution Level Control algorithms Estimation FDI algorithms Adaptation

SENSORS ACTIONS

ENVIRONMENT/ROBOTS


qualities variables

PROCESS (Including sensors and

actuators)

Intelligent supervisor Symbolic representation

Adapting Mechanism

Controllers

variables

exogenous

measured variables Level 0

Level 3

Level 2

Level 1

objectives

a priori knowledge


● Main attributes of an INTELLIGENT Main attributes of an INTELLIGENT

AUTONOMOUS CONTROL SYSTEM :AUTONOMOUS CONTROL SYSTEM :

◦ Perception of reality;

◦ Memorizing and Learning;

◦ Reasoning and Planning;

◦ Dynamic reconfiguration (hardware & software);

◦ Decision making and Behavior Generation.

● The hierarchical principlehierarchical principle with the distribution of

intelligence on different levels and layers is proper

for intelligent control systems.


● Functions to be identified at each abstraction level :

◦ PerceptionPerception (P)

◦ Knowledge representationKnowledge representation (K)

◦ Decision makingDecision making (DM)

● The output of each level is an actionaction sent to the

adjacent lower level :

[Pi; Ki; DMi] → Ai

or

[P;K;DM]n→ An [P;K;DM]n→ [P;K;DM](n-1) → A(n-1)


AUTONOMOUS AGENT

Planning of trajectory,internal representation, learning, global navigation

Coordination, adaptation learning,orientation, tasks distribution

Local navigationControl of moving (position, speed, acceleration)

ENVIRONMENT

AUTONOMOUS AGENTAUTONOMOUS AGENT

Planning of trajectory,internal representation, learning, global navigation

Coordination, adaptation learning,orientation, tasks distribution

Local navigationControl of moving (position, speed, acceleration)

ENVIRONMENT

AUTONOMOUS AGENT


● In systems of higher intelligence, the Behavior Behavior

Generation (BG)Generation (BG) modulemodule may interact with WMWM and

VJVJ modulesmodules to reason about space and time,

geometry and dynamics, and to formulate or select

plans based on values such as cost, risk, and goal

priorities

● The SP moduleSP module may interact with WMWM and VJ VJ

modulesmodules to assign values to perceived entities,

events and situations, and enable the other sub-

systems to determine preferences and make

choices


● These four sub-systems are totally connected into a

functional architecture and can exist as a system

that performs functions, and perpetuates its own

existence

WORLD

MODEL PERCEPTION

BEHAVIOR

GENERATION

SENSORS ACTUATION ENVIRONMENT

WORLD

MODEL PERCEPTION

BEHAVIOR

GENERATION

SENSORS ACTUATION ENVIRONMENT

VALUE JUDGEMENT


● Autonomous agentsAutonomous agents are computer systems that are

capable of independent action in dynamic

unpredictable environments

◦ their level of intelligence is not defined (if it exists)

◦ they do not have faculties of learning and self-

organization

● PlanningPlanning and reactive controlreactive control generate the

behavior

◦ feedforward controlfeedforward control (FFC) and feedback controlfeedback control

(FFB)

◦ deliberativedeliberative and reactivereactive actions as kinds of FFC and

FFB inclusion


● Knowledge for a mobile robot is represented by

a system of maps system of maps :

◦ Panner Map

◦ Navigator Map

◦ Pilot Map

● The upper level map (Planner’s Map) (Planner’s Map) should be

maintained for a long time due to the largest largest

scope scope and the “slow rhythm” “slow rhythm” of this level



Pilot MapPilot Map

● PERCEPTIONPERCEPTION :◦ Receiving and Organizing

◦ Clustering

◦ Generalization

◦ Pre-recognition

◦ Pre-estimation

● WORLD MODELWORLD MODEL :◦ Entity-relational

◦ Model formation

◦ Knowledge Base maintenance

◦ Estimation

◦ Learning


● BEHAVIOR GENERATIONBEHAVIOR GENERATION :

◦ Task Decomposition

◦ Scheduling

◦ Forecasting

◦ Comparison

◦ Selection

◦ Execution

● ACTUATIONACTUATION :

◦ Motion Generation

◦ Motion Coordination

◦ Motion Integration


Technological and Economic drivers;Technological and Economic drivers;

The decreasing cost of computation, networking and The decreasing cost of computation, networking and sensing;sensing;

The increasing require to use complex The increasing require to use complex infrastructures more efficiently;infrastructures more efficiently;

Environmental pressures will mandate the rapid Environmental pressures will mandate the rapid introduction of technologies to improve energy introduction of technologies to improve energy efficiency and reduce pollution; efficiency and reduce pollution;

Improving the health care systems for the Improving the health care systems for the increasing ageing population;increasing ageing population;

8. Cyber Physical Systems8. Cyber Physical Systems

Global warming, depletion for resources, Global warming, depletion for resources, ageing population and competition in a multi-ageing population and competition in a multi-polar world needs to accelerate the transition to polar world needs to accelerate the transition to a smarter and greener economy where the key a smarter and greener economy where the key input will be knowledge in action into complex input will be knowledge in action into complex CPS;CPS;

Computers and communication have become Computers and communication have become the “universal system integrator” that keeps the “universal system integrator” that keeps large systems together:large systems together:The national power grid; The national power grid; The air traffic control system;The air traffic control system;The national transportation network.The national transportation network.


Computer become ever-faster and communication Computer become ever-faster and communication bandwidth ever-cheaper, computing and bandwidth ever-cheaper, computing and communication capabilities will be embedded in all communication capabilities will be embedded in all types of objects and structures in the physical types of objects and structures in the physical environment;environment;

Cyber-physical systems (CPS) are physical, Cyber-physical systems (CPS) are physical, biological and engineered systems whose biological and engineered systems whose operations are monitored, coordinated, controlled operations are monitored, coordinated, controlled and integrated by computing and communication and integrated by computing and communication core: C2→C3→C4; (NSF report)core: C2→C3→C4; (NSF report)


CPS will be manifested from the nano-world to CPS will be manifested from the nano-world to large-scale wide-area systems of systems and at large-scale wide-area systems of systems and at multiple time scales;multiple time scales;

CPS – a new technological revolution is more than CPS – a new technological revolution is more than Networking and Information Technology → Networking and Information Technology → Information and knowledge in action integrated on Information and knowledge in action integrated on physical systems.physical systems.

Different visions in function of the research field;Different visions in function of the research field;


A new category of embedded systems where the A new category of embedded systems where the emphasis was made on the increased intersections emphasis was made on the increased intersections between the physical part and the computational between the physical part and the computational part of the system;part of the system;

““Cyber-Physical Systems are a next generation Cyber-Physical Systems are a next generation network – connected collection of loosely coupled network – connected collection of loosely coupled distributed cyber systems and physical systems distributed cyber systems and physical systems monitored/controlled by user defined semantic monitored/controlled by user defined semantic laws” – (the computer engineering community laws” – (the computer engineering community definition).definition).


Embedded computers and networks monitor and control the physical processes with feedback loops where physical processes affect computations and vice versa;

The design of such systems – requires understanding the joint dynamics of computers, software, networks and physical processes;

Intrinsic heterogeneity and complexity of CPS stresses all existing modeling languages and frameworks: Models of physical processes; Models of the software, computation platforms and networks; The models typically involve a large number of heterogeneous

components and composition semantics; The feedback loop between processes and computations

encompasses sensors, actuators, physical dynamics, computation, software scheduling and networks with contention and communication delays.


CPS introduces several challenges for system design:to support high system flexibility such that the

CPS components in the system are free to join or leave dynamically;

to support various Quality of Services (QoS) requirements through out every level of CPSs;

to support the large variable timing constraints for each component because of the non-deterministic system delay for sensing, computation, communication and actuation.


The following features are essential in a generic framework for CPS design, modeling and simulation:Heterogeneous application support;Various physical modeling environments;Scalability support – from small scale to large scale;Mobility support – support for modeling systems using

relevant properties; Integration of existing simulation tools; Integration of proprietary solutions and open standards

support;Software reuse;Usability.


We have to create an intelligent interface between cyber and physical worlds – rethink or reinvent interface functions such as coordination, integration, monitoring and control;

Advances in the cyber world such as communications, networking, sensing, computing, storage and control, as well as in the physical world such as materials, hardware and renewable “green” fuels are all rapidly converging to realize this class of highly collaborative computational systems that are reliant on sensors and actuators to monitor and effect change.


Cyber capabilities are embedded in every physical process and component, networking is employed at multiple and extreme scales, complexity lies at multiple temporal and spatial scales;

Advances in CPS can make applications faster more spatially and temporally precise, robust to hostile or inaccessible environments, perform distributed coordination of large scale systems;

Research gaps, such as human behavior abstraction and representation and bridging natural language representation and formal language framework, are needed for CPS design, development and operation;

Dramatic and rapid changes in engineering practice and education are needed to insititutionalize the advances of CPS.


The role of key academic disciplines, including sensing, networking, communications, control, safety and security in CPS foundations, methods, tools and applications will be explored;

Event-based systems design should be a good way to follow for CPS, defining a CPS event model, which incorporates the spatio-temporal attributes and observer information into the event definitions;

A typical CPS mainly consists of the following components: physical objects, sensors, actuators, communication networks and computing devices (e.g. controllers). Sensors and actuators are organised as large wired and wireless networks. CPS facilitates interplay of the cyber and phisical systems, that is , control of phisical environments;

The use of WSAN distinguishes CPS from traditional embedded systems and wireless sensors networks.


From a networking viewpoint, some widely- recognized characteristics of CPS can be outlined as follows:Network Complexity – the network of a typical CPS is

often large in scale because of the large number of distributed nodes in the systems.

Resource Constraints – the embedded devices are always limitedin computing speed, energy, memory and network band width.

Hybrid Traffic and Massive Data – the large number of sensors and computing nodes generate a huge volume of data of various types.

Uncertainty – in CPS are many factors that could potentially cause uncertainty – sensors measuremens error, computational model error, software defect, unveliable of wireless communications and changes in network topology.


The success of a large number of CPS applications heavily relies on the QoS provided by the employed networks WSAN for CPS have to deliver massive date within hybrid traffic in a proper manner with the presence of network complexity, resource constraints and uncertainty;

Cyber Physical Systems are becoming ubiquitous, pervading every sector of the critical national infrastructure and every aspect of an individual’s daily life, including the following examples: Medical care and health, Energy, Transportation and Mobility, Manufacturing, Materials and other sectors;

CPS are “systems of systems” whose interaction are exponentially complex;

Cross sector cooperation is needed to develop the common CPS science and technology foundation.


Distributed Distributed Cyber-Physical Cyber-Physical

Information Information Distillation andDistillation and

Control Systems (ofControl Systems (of Embedded SystemsEmbedded Systems))

Integration at Integration at ScaleScale

AutonomyAutonomy

Device/Data Device/Data ProliferationProliferation

Scale Challenges → Composition Scale Challenges → Composition ChallengesChallenges


Sensor Networks Medical Devices

Industrial Applications Actuator Networks

Embedded Everywhere!

Data/Device Proliferation

World Wide

Sensor Web

Smart Building Environment

Future Combat System

Integration & ScalingChallenges

High endLow end

Ubiquitous embedded devices

• Large-scale networked

Embedded systems

• Seamless integration with a physical environment

Complex systems with global integration

• Global Information Grid

• Smart Building Environment

Integration at Scale

CPS Unit

User defined Semantic Laws

Computation

System StateTransition?

CPS Unit

User defined Semantic Laws

Computation

System StateTransition?

Sensor Units

Preset SensorControl LawsComputation

Sensors

Si(t)

Actuator Units

Preset ActuatorControl LawsComputation

Actuators

Ai(t)

Next-generation network

Publish Sensor Events / Actuator Events / Information

Receive System / User Command Receive Actuator EventsSubscribe Interested Events / Information

Some Aspects of the Physical World

Affecting

Humans

Sampling Changing

Humans

Subscribe Interested

Network nodesNetwork nodesNetwork nodes

Publish Sensor Events

Live Events /

Information

Live Events /

Information

YESYES

Tightly

Coupled

(Optional)

Tightly

Coupled

(Optional)

Changing

Physical

World

NO NO

Secured knowledge Database Servers

YES YES

Events / Information

Publish Actuator Events / Information Publish Actuator Events / Information

Event / Information World

An abstraction of

The real-time

Physical world

Real-Time

Context Aware

Logics

Subscribe Interested Events / Information

Out-of-Date

Events & Information

Christophe Tricaud - 2010

Intelligent Systems Architecture for Manufacturing

Computational thinking and integration of Computational thinking and integration of computation around the physical dynamic computation around the physical dynamic systems form CPS where sensing, decision, systems form CPS where sensing, decision, actuation, computation, networking and physical actuation, computation, networking and physical processes are mixed – (the vision of the control processes are mixed – (the vision of the control systems community).systems community).


Computing

CPS - allow individual machines to work together to form CPS - allow individual machines to work together to form complex systems that provide new capabilities, make complex systems that provide new capabilities, make

systems safer and more efficientsystems safer and more efficient

Physical

Computation

CommunicationContro

l

Information and

knowledge

CYBE

R

PHYSICAL

SYSTEMS

Communication

Biological Control

CPS → ICPS

C4 → ICPS


Cyber capability – networking and computational Cyber capability – networking and computational capability → in every physical component;capability → in every physical component;

CPS are networked at multiple and extreme scales;CPS are networked at multiple and extreme scales;

CPS are complex at multiple temporal and spatial CPS are complex at multiple temporal and spatial scales, are dynamically reorganizing and scales, are dynamically reorganizing and reconfiguring;reconfiguring;

Control needs to be dependable and certifiable in Control needs to be dependable and certifiable in certain cases; certain cases;


Control loops are closed at each spatial and Control loops are closed at each spatial and temporal scale;temporal scale;

Operation needs to be dependable and certifiable in Operation needs to be dependable and certifiable in certain cases;certain cases;

Computation/Information and Knowledge Computation/Information and Knowledge processing and physical processes are so tightly processing and physical processes are so tightly integrates that it is not possible to identify whether integrates that it is not possible to identify whether behavioral attributes are the result of behavioral attributes are the result of computations, physical laws or both working computations, physical laws or both working together.together.


Cyber-physical coupling drivers by new demands Cyber-physical coupling drivers by new demands and applicationsand applicationsCyber capability in every physical component;Cyber capability in every physical component;Large scale wired and wireless networking;Large scale wired and wireless networking;Networked at multiple and extreme scales.Networked at multiple and extreme scales.

Systems of systems Systems of systems New spatial-temporal constraints;New spatial-temporal constraints;Complex at multiple temporal and spatial scales;Complex at multiple temporal and spatial scales;Dynamically reorganizing/reconfiguring;Dynamically reorganizing/reconfiguring;Unconventional computational and physical substrates Unconventional computational and physical substrates

(Bio? Nano?)(Bio? Nano?)


Novel interactions between Novel interactions between communication/computing/control and communication/computing/control and cognition:cognition:High degree of automation, control loops High degree of automation, control loops

must closed at all scales;must closed at all scales;

High level of autonomy and total faults High level of autonomy and total faults tolerant.tolerant.


Applications

of CPS

Tele-physical services

Medical devices

and systems

Automotiveand air

traffic control

Environmentalmonitoring

Cooperative robotics

Smart buildings

Advanced manufacturing

Supply networks and

cyber-networksAutomotive

transportation

Critical infrastructure and industry

Communication and data

fusion

Applications Applications of CPSof CPS

CPS will require the implementation of distributed CPS will require the implementation of distributed and embedded applications;and embedded applications;

CPS are globally virtual and locally physical → CPS are globally virtual and locally physical → provides a unified view from local components to provides a unified view from local components to global systems;global systems;

CPS constitute one of the next big challenges of the CPS constitute one of the next big challenges of the engineering community;engineering community;

CPS – computers, networks, devices and their CPS – computers, networks, devices and their environments in which they are embedded have environments in which they are embedded have interacting physical properties, consume resources, interacting physical properties, consume resources, and contribute to the overall system behavior. and contribute to the overall system behavior.


ACPS may be modeled as a hybrid system where ACPS may be modeled as a hybrid system where physical processes are represented as continuous physical processes are represented as continuous time models of dynamics and computations are time models of dynamics and computations are described using state machines, dataflow models, described using state machines, dataflow models, synchronous/reactive models and /or Discreet synchronous/reactive models and /or Discreet Event models;Event models;

Object – oriented design principles can be adapted Object – oriented design principles can be adapted to CPS models using the notion of actor – oriented to CPS models using the notion of actor – oriented classes;classes;

Modeling Interaction of Functionality and Modeling Interaction of Functionality and Implementation – Effect of networks and Implementation – Effect of networks and computing;computing;

Aspect – oriented programming (AOP) applied to Aspect – oriented programming (AOP) applied to conjoining models of functionality and conjoining models of functionality and implementation ;implementation ;


The CPS requires strategies that facilitate The CPS requires strategies that facilitate composition of components that are separated in composition of components that are separated in space – “Modeling Distributed Behaviors”;space – “Modeling Distributed Behaviors”;

Must to provide well-defined actor-oriented Model Must to provide well-defined actor-oriented Model of Computation (MoC) with well – defined of Computation (MoC) with well – defined semantics – to integrate semantics – to integrate actor – oriented models actor – oriented models (AOM) (AOM) with practical and realistic notions of time. with practical and realistic notions of time.


The design of CPS is much more than union designing The design of CPS is much more than union designing of both computational and physical systems (I.P.C.D.);of both computational and physical systems (I.P.C.D.);

A new science of CPS design:A new science of CPS design:Will allow us to create new machines with complex Will allow us to create new machines with complex

dynamics and high reliability;dynamics and high reliability;Will allow us to be able to apply the principles of CPS to Will allow us to be able to apply the principles of CPS to

new industries and applications in reliable and new industries and applications in reliable and economically efficient way. economically efficient way.

New science of CPS will allow us:New science of CPS will allow us:To design systems more economically by sharing both To design systems more economically by sharing both

abstract knowledge and concrete tools;abstract knowledge and concrete tools;To design more dependable CPS, since we can apply best To design more dependable CPS, since we can apply best

practices to the entire range of cyber-physical practices to the entire range of cyber-physical applications.applications.


New science and technology of cyber/physical New science and technology of cyber/physical systems can be guided by the following major systems can be guided by the following major challenges:challenges:Realign abstraction layers in design flows: Realign abstraction layers in design flows: Computations Computations

abstraction need to include physical concepts such as abstraction need to include physical concepts such as time and energy. Abstractions developed for describing time and energy. Abstractions developed for describing physical dynamics should be extended to capture physical dynamics should be extended to capture uncertainties of implementation platforms, such as uncertainties of implementation platforms, such as network delays, finite world length and round-off errors;network delays, finite world length and round-off errors;

Develop semantic foundations for composing Develop semantic foundations for composing heterogeneous models and modeling languages heterogeneous models and modeling languages describingdescribing different physics and logics. different physics and logics.

9. Science and Technology Challenges9. Science and Technology Challenges

Must to introduce or develop mathematical Must to introduce or develop mathematical frameworks that make semantics not only frameworks that make semantics not only mathematically precise but also explicit, mathematically precise but also explicit, understandable and practical for system developers as understandable and practical for system developers as well as tools developers;well as tools developers;

Develop new understanding of compositionality in Develop new understanding of compositionality in heterogeneous systems that allows us to take into heterogeneous systems that allows us to take into account both physical and computational properties;account both physical and computational properties;

New science and technology foundation for system New science and technology foundation for system integration model-based, precise and predictable → integration model-based, precise and predictable → new science-based engineering discipline.new science-based engineering discipline.

New theories and methods for compositional New theories and methods for compositional certification of CPS;certification of CPS;

New infrastructure for agile design automation of CPS;New infrastructure for agile design automation of CPS;


Develop new open architectures for CPS → to build Develop new open architectures for CPS → to build national-scale and global-scale capabilities:national-scale and global-scale capabilities:CPS will transform our world with systems that CPS will transform our world with systems that

respond more quickly, are more precise (robotic respond more quickly, are more precise (robotic surgery and nano-tolerance manufacturing), work in surgery and nano-tolerance manufacturing), work in dangerous or inaccessible environments provide large-dangerous or inaccessible environments provide large-scale distributed coordination, are highly efficient, scale distributed coordination, are highly efficient, augment human capabilities (assistive technology and augment human capabilities (assistive technology and ubiquitous healthcare monitoring and delivery). ubiquitous healthcare monitoring and delivery).

C2 → C3 → C4 → ICPSC2 → C3 → C4 → ICPSWe need to rethink industry and manufacturing for We need to rethink industry and manufacturing for

the 21th century the 21th century The traditional disciplinary boundaries need to be The traditional disciplinary boundaries need to be

realized in all levels of training and educationrealized in all levels of training and education


System Complexity System Complexity Increasing functionality;Increasing functionality;Increasing integration and networking interoperability;Increasing integration and networking interoperability;Growing importance and reliance on software ;Growing importance and reliance on software ;Increasing number of non-functional constraintsIncreasing number of non-functional constraints

Nature of tomorrow’s systems Nature of tomorrow’s systems Dynamic, ever-changing, dependable, high-confidence;Dynamic, ever-changing, dependable, high-confidence;Self-aware, self-adapting, self repairing and self sustainingSelf-aware, self-adapting, self repairing and self sustaining

CPS – everything, used by everyone for everythingCPS – everything, used by everyone for everything24/7 – availability;24/7 – availability;100% reliability;100% reliability;100% connectivity;100% connectivity;Remember everything forever;Remember everything forever;Individuals, specials, social networks, cultures, Individuals, specials, social networks, cultures,

populations…populations…

10. Trends in Systems Science and Scientific 10. Trends in Systems Science and Scientific Challenges Challenges

Computations and Abstractions:Computations and Abstractions:Computational abstractions;Computational abstractions;Novel real-time embedded systems abstractions for CPS;Novel real-time embedded systems abstractions for CPS;Compositional frameworks for both functional, temporal Compositional frameworks for both functional, temporal

and non-functional properties;and non-functional properties;Robustness, safety and security of CPS.Robustness, safety and security of CPS.

Compositionality: Compositionality: Composition and interoperation of CPS;Composition and interoperation of CPS;Compositional frameworks for both functional, temporal Compositional frameworks for both functional, temporal

and non-functional properties;and non-functional properties;

Systems and Network Supports:Systems and Network Supports:CPS architecture, virtualization;CPS architecture, virtualization;Wireless and smart sensor networks;Wireless and smart sensor networks;Predictable real-time and QoS quarantees at multiple Predictable real-time and QoS quarantees at multiple

scalescale


New foundations:New foundations: New theory of systems;New theory of systems;Control (distributed, multi-level in space and time) and Control (distributed, multi-level in space and time) and

hybrid systems – cognition of environments and hybrid systems – cognition of environments and systems-state and closing the loop;systems-state and closing the loop;

Dealing with uncertainties and adaptability, Dealing with uncertainties and adaptability, environments and resource availability;environments and resource availability;

Scalability, reliability, robustness, stability of systems;Scalability, reliability, robustness, stability of systems;Science of certification – evidence-based certification Science of certification – evidence-based certification

measures of verification, validation and testing.measures of verification, validation and testing.

New notions of “correctness” and “compositionality” New notions of “correctness” and “compositionality” of softwareof softwareSystems Software and network supportsSystems Software and network supports


New formal models and logics for reasoning about CPS;New formal models and logics for reasoning about CPS;New verification/analysis tools usable by domain New verification/analysis tools usable by domain

engineers;engineers;New engineering design techniques and tools:New engineering design techniques and tools:

Modeling and analysis, requirements capture, hybrid Modeling and analysis, requirements capture, hybrid systems, testing….;systems, testing….;

Capture and optimization of interdependencies of different Capture and optimization of interdependencies of different requirements. requirements.

Validation and certification:Validation and certification: Metrics for certification/validation;Metrics for certification/validation;Evidence-based certification, incremental certification.Evidence-based certification, incremental certification.

The emerging cyber-physical systems shall enable a modern grand vision for new societal-level services that transcend space and time at scales never possible before.


We need a new Control Theory to analyze and design the complex CPS → including marriage of control, information an communications, and theoretical computer science and physical processes;

Develop new architectures of autonomous control systems by integration all intelligent methodologies as an associative hybrid system;

Develop the agent technology, architectures based design, distributed embedded systems;

Integration of intelligent agents into hierarchical and heterarchical architectures with different time-scale and resolution → create new generation of Autonomous Complex Control Systems

11. Conclusion

CPS will transform our world with systems that Respond more quickly;Are more precise (robotic surgery and

nanotolerance manufacturing);Work in dangerous or inaccessible environments;Provide large-scale distributed coordination;Are highly efficient, augment human capabilities

(assistive technologies and ubiquitous healthcare monitoring and delivery).

11. Conclusion

Thank you!Thank you!

1. cyber phisical systems - interdisciplinary vision

Documents

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