harware in the loop simulation uuv ieee siemens

8/10/2019 Harware in the Loop Simulation UUV IEEE Siemens

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Hardware In The Loop Simulation Applied To

Semi-Autonomous Underwater VehiclesHilgad Montelo, Celso Massatoshi Furukawa

University of So Paulo

[email protected], [email protected]

Abstract-Unmanned Underwater Vehicles (UUVs) have manycommercial, military, and scientific applications because of theirpotential capabilities and significant cost-performanceimprovements over traditional means of obtaining valuableinformation about the underwater environment. Thedevelopment of a reliable sampling and testing platform forthese vehicles requires a thorough system design and manycostly at-sea trials during which systems specifications can bevalidated. Modeling and simulation provide a cost-effectivemeasure to carry out preliminary component, system (hardwareand software), and mission testing and verification, therebyreducing the number of potential failures in at-sea trials. Anaccurate simulation environment can help engineers to findhidden errors in the UUV embedded software and gain insightsinto the UUV operation and dynamics. This work describes the

implementation of a UUV's control algorithm usingMATLAB/SIMULINK, its automatic conversion to anexecutable code (in C++) and the verification of its performancedirectly into the embedded computer using simulations. It isdetailed the necessary procedure to allow the conversion of themodels from MATLAB to C++ code, integration of the controlsoftware with the real time operating system used on theembedded computer (VxWorks) and the developed strategy ofHardware In the Loop Simulation (HILS). The Maincontribution of this work is to present a rational framework tosupport the final implementation of the control software on theembedded computer, starting from the model developed on anenvironment friendly to the control engineers, like SIMULINK.

I. INTRODUCTION

Traditional tests, many times refereed as static tests, are the

evaluation of functionalities of a particular component where,to it, are provided measurable inputs and outputs. The

growing of the demand for new products faster and a

consequent reduction of the development cycles associated to

the projects, has caused a increase on necessity to execute

dynamic tests, where the behavior of each component is

evaluated at same moment of its interaction with the rest of

the system and environment. Dynamic tests, in [7], minimize

risks related to the security and costs, covering more tests

conditions when compared to static tests. The application of

the test approach involving components of hardware,

software and dynamic or behavioral conditions is called

HILS.

The HILS, described by [3], is a tool that comes to aid the

work of the controls engineer. Unnumbered systems could

be developed faster only using an initial conceptual model

developed adapting or adjusting the necessary controls

variables (for instance: maximum supported pressure,

maximum speed, minimal temperature, maximum depth, bus

clock, minimal systems memory, etc), where a set of them

could be encapsulated into a configurations profile, validated

in a simulated or basic prototype, and, finally, verified in a

final target. Into this environment, the controls engineer

could to dedicate more time analyzing and detailing features

to solve the control problems related to the project, avoiding

the necessity to take much time writing or debugging lines of

firmwares code or even the necessity to handle with

complexities like time restrictions, establishment of priorities

or techniques to tasks scheduling.

The HILS approach could be applied to all systems, for

research and development; in the most assorted areas, like

military, medicine, automotive, air space, like indicated by

[1], [5], [9], [13], [20]... or even in projects where interactions

between a product in development and its environment of

operation (part of the real world) are not so simple to

represent formally, like some models described by [10], [15],

[18], [21], [22].

The objective of this work is to present a rationale

approach to assist control engineers during the development

of a semi-autonomous underwater vehicle, vehicles that can

perform part of their operations with or without human

intervention, improving the integration between complex

subsystems like: navigation, power management, actuation,

sensing, etc all together working in an unpredictable and,

many times, hazardous environment.

II. METODOLOGY

The approach to build an appropriate hardware in the loop

simulation architecture applied to a semi-autonomous

underwater unmanned vehicle consists of the construction

following environments, tools and modeling:

Development Environment: It consist, specifically, of the

assembly and utilization of a hardware with similar features

(preferentially) to those presented by the unmanned

underwater vehicle in development in the laboratory of

mechatronic engineer at Polytechnic School of So Paulo

(Escola Politcnica de So Paulo - EPUSP), allowing to make

a good utilization of the resources and solutions already in

research like described in [2], [8], [11], [12].

Real Time Operating Environment: VxWorks is a realtime operating system manufactured by Windriver Systems

and initial description could be found in [19]. Like others real

time operating systems, it includes a kernel that supports

multiple tasks and preemptive scheduling. Very popular in

embedded applications and widely used in a variety of


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hardware architectures like: MIPS, PowerPC, SH-4, ARM,

StrongARM, xScale, and x86.

Real Time Framework: The Constellation consists of an

object oriented real time framework that provides capabilities

to interfacing and code generation from a model developed in

MATLAB/Simulink. The Constellation framework is

specified in [6]. The model could be converted in ANSI C++

programming language using all advantages of the objected

oriented programming and yet a high performance. The real

time capabilities are found in a middleware interface,

between the generated code and the real time environment.

The MATLABs real time workshop provides the necessary

elements to perform that relationship.

UUVs Dynamic: One of the first steps to realize an

appropriate simulation consists of the modeling of the

dynamic equations of the Hornet UUV, specified in [4] and

used in this work as a concept prove, due the fact that UUVs

model presents a simpler system of equations appropriate to

develop the necessary software interfaces to be used also by

others UUVs. The Fig. 1 presents the six degrees and the

respective derivatives used by a rigid body and its system of

coordinates in the Hornet UUVs model. Where: is the

linear movement relationship to the longitudinal axis; is thelinear movement relationship to the transversal axis; is the

linear movement relationship to the vertical axis; is the

angular or rotational movement over the axis; is the

angular or rotational movement over the axis and is the

angular or rotational movement over the axis.

The inputs of the system are defined by the following set of

forces: : force applied by lateral thruster, : force applied

by frontal thruster, : force applied by vertical thruster,

: external disturbs or interferences like water

current for instance, linear hydrodynamic drag

force as defined in (1), and studied by [16].

Where:

: Drag coefficient.

: Waters density.

: Projected area of drag.

: Velocity of the surface of drag.

The dynamic equations used to describe the vehicles

movement are developed in accordance with [14]. Taking the

sum of all forces in direction of the respective axis

(X, Y, Z), and solving its equations for acceleration,

presented, respectively, by (2), (3), and (4).

Where:

: Acceleration over X axis.

: Acceleration over Y axis.

: Acceleration over Z axis.

: Velocity over X axis.

: Velocity over Y axis.

: Angular velocity over Z axis.

: Linear hydrodynamic drag forceover the X axis.

: External disturbs over the X axis.

: Linear hydrodynamic drag force

over the Y axis.

: External disturbs over the Y axis.

: Linear hydrodynamic drag force

over the Z axis.

: External disturbs over the Z axis.

: Considering that there are not

disturbances.

: Vehicles mass.

: Vehicles weight in water

(Considering that the buoyancy

force is 0).

And taking the sum of the moments over the axis, it is

obtained the acceleration around that axis presented by (5):

Where:

: Angular acceleration over Z axis.

: Distance between the thrusters 1

(lateral thruster) and 2 (frontal

thruster): Sum of the moments over Z axis

(Considering that there are not

disturbance over Z axis).

: Moment of inertia over Z axis.

Fig. 1. Rigid body and its coordinate system.


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For the simulation purposes those movement equations

contains eight state variables, represented by the vector

and three inputs independently

controlled represented by presented by (6):

=

The transformation matrix presented in (7) is responsible to

convert the output states of the rigid body found in the plant

model into the coordinate values associated to a geographic

reference in the horizontal plan.

To obtain the coordinates in the vertical plan, it is sufficient

to calculate the superposition matrix of .

The Fig. 2 shows the block diagram used to represent the

depth controller. The vehicle receives a command with the

desired depth ( ), it verifies the current depth

( ) and apply an output to the thruster 3 ( ).

Analyzing (4), it is possible to see that the relationship

between the depth and the actuator responsible to adjust it (in

this case, the thruster 3) is simple and linear; therefore a PID

(Proportional-Derivative-Integral) controller is sufficient

[23].

Where:

: Command of depth used by the mission

planner;

: Current depth gathered by the navigation

system;

: Depth error;

: Vertical thruster output;

: Proportional gain;

: Integral gain;

: Derivative gain.

A PID controller is also provided to establish the velocity

control; the velocity is obtained directly from the thruster (T1)

instead the desired velocity produced by the mission planner

This approach is used to minimize problems of accuracy

due utilization of estimated values. The velocity and direction

controller work together where, depending of the current

directions value, it is possible to increase or decrease the

vehicles velocity.

To control the vehicles direction, it was used a slide-mode

control, presented by Fig. 3 and also used by [24], that allows

errors in its sliding layer with about +/- 3 degrees and sliding

function defined by (8).

The direction controller uses the following parameters:

: Direction angle used by the mission

planner;

: Current UUVs direction angle;

: Positive and negative limits used over thethruster output;

: Error gain;

: Error rate gain;

and : Horizontal thrusters output.

The direction controller uses the sliding function presented

by (8), to decrement the error and error rate down to zero.

Where:

: Slide mode function;

: It is a bi-dimensional array with the controllersgains;

: It is a bi-dimensional array that contains the

controllers error and error rate

Hardware In the Loop Simulation Environment: The

Fig. 4 shows a general overview of the HILS architecture

used to assist the development and construction of a semi-

autonomous underwater vehicle. It contains the main

components:

Embedded Hardware: It represents a clone of part of

the hardware used to produce the UUV. The inputs

consists of the forces generated by the environment

(like current, pressure, buoyancy, etc) and the forces

generated by the thrusters; World Model: It consists the model used to represent

the physical world or, more precisely, a very close

representation of where the UUV will operate;

Control Parameters: They are the main and auxiliary

variables used to operate adequately the control

Fig. 2. Block Diagram of the PID depth controller..

Fig. 3. Block Diagram of the slide-mode direction controller.


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algorithms used by the UUV (For example: initial

velocity, initial acceleration, Initial position, erroradjusts for directions, maximum pressure allowed,

etc);

Sensors and Actuators: They represent the components

that allow the inputs and outputs of the system,

respectively. They could be real components

(hardware like compass, inclinometers, temperature

sensors, pressure sensors) or virtual (represented by

input/output files, for instance).

Data Logger: This component is responsible to register

all operations that are using this infra-structure, either

through a partial or total simulation. Only using the log

files and registers produced by this component is

possible to evaluate if a control algorithm is adequate

for the UUV and its environment of operation.

The following steps are necessary to generate a useful code

compatible with the proposal of hardware in the loop

architecture, based in an initial UUV's conceptual model.

To prepare the UUV's control model in Simulink

environment: It consists in the utilization of the

Simulink tool box and its control blocks (like S-

Functions, PID block, Plant block, etc). OBS: Before

the next step, it is important to eliminate any algebraic

loop in the model (algebraic loops occur when an input

port with direct feed through is driven by the output of

the same block, either directly, or by a feedback path

through other blocks which have direct feed through); To convert the prepared UUV's control model in a

suitable software component compatible with the real

time framework adopted. There is a special tool

developed to achieve that objective where is possible

to specify event handlers, allows priority specification

and concurrent code;

To prepare the target environment and to configure

its real time operating system to establish all

necessary connections;

To configure the real time framework to operate

either with the operating system in target machine or

with a simulation environment (environment with the

same interfaces but not considering time restrictions);

To establish connection between the target machine

and the Matlab/Simulink environment using the

middleware provided by Constellation tools;

Trough the Data Logger component and tools like the

Matlab's shell, WindView or Stethoscope, see [17]; is

possible to evaluate and even update values of

monitored variables or statuses in run time to achieve

the timers and specified control conditions;

All generated firmware's code is in ANSI C++ not

allowing the utilization of templates (generic

programming) or even dynamic memory allocation

(temporally to avoid problems with garbage

collection, for instance).

III. RESULTS

The dynamic model and its respective control algorithm,

published in [4], were successfully reproduced in

Matlab/Simulink environment, without any behavioral loss,

even after the elimination of undesired algebraic loops.

The hardware in the loop environment and the UUV's

controller was embedded in a hardware developed in PC104

standard, using x86 architecture, the same configuration

presented by the UUV in development. Virtual sensors and

virtual actuators (like compass, inclinometers, depth's

sensors, thrusters, etc) also had its embedded and real time

representation stored directly into the target's file system.

For all graphs generated, the following procedure was

executed:

All sensors have their values recorded in files. The code generated for the controller reads the value

of those files (sensor values) and, after the necessary

calculus, generates the actuation signals for the UUV's

thrusters.

The actuation signals were also recorded in files, used

later as input for the dynamic simulator. They contain

information about velocity control, direction control,

and depth control.

To compare the results obtained with the implemented

HILS (identified by the label: "Reproduced") against

the adopted bibliographic material (identified by the

label: "Source").

The Fig. 5 shows a direction graph of the path traversed by

the UUV from the start point (point: X=0 and Y=0) in

direction to the point indicated by the beacon (point: X=35

and Y=35). The trajectory performed by the UUV in HILS

environment is similar and compatible with the results

presented by [4].

Fig. 4. Overview of the HILS used to assist the development of UUV.

harware in the loop simulation uuv ieee siemens

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