batch process controfinal

8/7/2019 BATCH PROCESS CONTROfinal.

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PRESENTED BY-

VIJAY PRATAP SINGH2009 EE05(C&I)MNNIT,ALLAHABD

BATCH PROCESSCONTROL(SEQUENTIALAND LOGIC CONTROL)


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A processes in which sequence of operation is carried outto produce a quantity of product(the batch) and in whichthe sequence is repeated to produce further batches is called

batch or sequential processBatch processing typically involves raw materials that are

combined to mix or react in a certain sequence over a

period of time to produce the completed output.A sequence of one more steps (recipe) usually carried outin more than one vessel and in a defined order, yielding afinished product.


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Electronic materialsSpecialty chemicalsMetals

CeramicsPolymersFood and agricultural materialsBiochemical's

Batch process are widely use in chemical industry andfood processing. where the operation carried outfrequently involves raw material carrying out reaction of two other chemicals at specified temperature

BATCH PROCESSING USE IN

MANUFACTURING


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levels of process control andoptimization in manufacturing


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In a batch reactor the reactants and the catalyst are placed in the reactor which is then closed to transportof matter and the reaction is allowed to proceed for agiven time whereupon the mixture of unreactedmaterial together with the products is withdrawn .


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.

A chemical is produced by the reaction of two other chemicals at specified temperature. The two chemicalare mixed together in a reactor and feeding hot or coldwater through water jacket, which surround the

vessel, control the temperature of reaction. the flow of chemical into reactor and flow of product mix out of reactor are controlled by adjusting the respectivevalves.


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Batch Mixing Tank-OperationsSequence1. Introduce liquid A until level reaches LH22. C lose A valve, open B valve and start mixer

3. W hen level reaches LXH2, stop flow of B and themixer and open discharge valve (VN9)

4. Discharge product until level reaches LL2, thenclose the discharge valve .


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1 0

INF ORMAT ION FL OW D IAGRAM


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ON THE BASIS OF NUMBER OF PRODUCT

Single -product batch processMulti-grade batch processMulti-product batch process

ON THE BASIS OF STRUCTURE

Series (single stream)Parallel (multi- stream )

CLASSIFICATION OF BATCH PROCESSING


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A Multi-grade batch process product that are similar butdiffer only in formula quantities. The same operation are

performed in each batch but the quantity of raw materialand processing condition are varied.


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A Multi-product batch process produces product utilizingdifferent methods of production are control. In this boththe procedure and formula changed


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A parallel batch process structure is that in which several batchesmay be executing at same time as shown in figure (b). And theycould be performing the same operation

PRALLEL BATCH PROCESS


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SERIES PARALLEL

BATCH PROCESSES


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Multi-Product Processing Overview

18

Fab Tool

Process 2

Fab Tool

Process 1

Process 2

Fab Tool

Process 1

Process 1AB BB

A A A A

A A

AB BBA A


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Control of batch processes differs from control of continuous processes in two main ways.

Since batch processes have no steady-state operating point,the set point and control signals correspond to time-varying profiles.

batch processes are repeated over time and arecharacterized by two independent varia bles, the run time tand the run counter k.


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xk (t ) = F (xk (t ), u k (t )), x k (0) = x(0) k Yk (t ) = H (xk (t ), u k (t)),

Z k = Z(x k [0, t f ], u k [0, t f ]),whereT denotes the run timeK denotes the run index

X represents the state vector U is the input vector


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There are two types of control objectives.Online implementation .

1.O nline control of run-time outputs2. O nline control of run-end outputs

run-to-run implementation .

3 . Run-to-run control of run-time outputs4. Run-to-run control of run-end outputs


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This control approach is similar to that used in

continuous processing. However, although somecontrolled variables, such as temperature in isothermaloperation, remain constant, the key processcharacteristics, such as process gain and time

constants, can vary considerably because operationoccurs along state trajectories rather than at a steadystate operating point.u k(t ) = K(Y k(t ), Yref(t ))

ONLINE CONTROL OF RUN TIME

OUTPUTS


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it is necessary to predict the run-end outputs z based onmeasurements of the run-time outputs y. Model

predictive control (MPC) is well suited to this task The controller can be written asU

k (t ) = P (Zpred,k(t ), Zref), (2)where P is the online control law for run-end outputs andZpred, k(t ) is the prediction of z available at time t for

batch k.

ONLINE CONTROL OF RUN ENDOUTPUTS


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The manipulated variable profiles can be generated usingiterative learning control (ILC), which exploits

information from previous runs. This strategy exhibitsthe limitations of open-loop control with respect to thecurrent run, in particular, the fact that there is nofeedback correction for run-time disturbanceU

k+1 [0, t f ] =I(y k [0, t f ], yref [0, t f ])where I is the iterative-learning control law for runtime outputs.

ILC uses the entire profile of the previous run to generate the input profile for the next run.

RUN TO RUN CONTROL OF

RUN TIMES OUTPUT


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In this case the input profiles are parameterized as uk[0,tf ] = U( k) using the input parameters k. The batch

process is thus seen as a static map between the input

parameters k and the run-end outputs Zk.The controller is written asU

k+1 [0, t f ] = U ( k+1 )

k+1 = R (Z k , Z ref )where U represents the input parameterization and R isthe run-to-run control law for run-end outputs.

RUN TO RUN CONTROL OF RUNEND OUTPUT


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BATCH CONTROL SYSTEM


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Abs ence of s teady s tate and pre s ence of con s traint s .

In batch processing, operations proceed from an initial state toa ver y different final state . Hence, there exists no singleoperating point around which the control s y stem can bedesigned . C onsequentl y , for control design and optimization, itis not possi ble to use approximate models by linearizationaround a single O perating point .

CHARACTERSTICSOF BATCH PROCESS


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R epetitive nature


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A state diagram represents a state machine. A state machine hasa number of states. Each state is either active or passive. Only one

state is active at a time. The state machine always starts in aparticular state defined as the initial state, and it ends (stops)after the final state.

STATE DIGRAM


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Action 2: Motor M1 runsState 2 actions:Action 1: Valve V1 is closed

Action 2: Heater H1 is on


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Transitions brings the state machine from one state to another. Atransition can go only from an active state which is presentlyactive. A transition takes place only if its transition condition isTRUE. Transition conditions are in the form of logical expressions

having value either TRUEOr FALSE and may be listed as indicated below:Transition T_Init_ 1 : Button_start = ON.Transition T_ 1 _2: L 1 > Level_High;

where Transition T_ 1 _2 means the transition from state S 1 to stateS2. A transition condition may be written directly in the statediagram. For example, the expressionT_Init_ 1 : Button_start = ON


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Sequential function charts (SF C s) are similar to Statediagrams . O ne small difference is that a transition condition isindicated by a small line in the transition path from one stateto another . And, t y picall y , the states are denoted steps, whichare represented by rectangles .

SEQUENTIAL FUNCTIONCHART


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Production amounts are usually smaller than for continuous processing.

Requires reduced inventories and shorter responsetimes.

Final product quality must be satisfied with each batch(no blending).

M ore emphasis on production scheduling in batchprocessing .

Batch processing is suitable for production systemwhere product are made in low v olume.


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REFERENCES

1 . COMPUETR AIDED PROCESS CONTROL BY S.K. SINGH2. IEEE CONTROL SYSTEMS MAGAZINE 2006

3 . Control of Batch Processing Systems BY Haresh Gurnmi, RaviAnupindi and Ram Akella Graduate Scliool of IndustrialAdministration, Carnegie Mellon Universit.y, Pittsburgh, PA 1 5213

4. Instrument Engineers' Handbook: Process control andoptimization By Bela G. Liptak, Bla G. Liptk, page no. 1 53 5

5. BATCH PROCESS CONTROL STRATEGIES BY S. Macchietto,Centre for Process Systems Engineering, Imperial College, London

6. 200 8 1 0th Intl. Conf. on Control, Automation, Robotics and VisionHanoi, Vietnam, 17 20 December 200 8 by Jie Zhang, Jerome

Nguyan, Newcastle University7 . Issues Surrounding Supervisory Control of Batch Manufacturing

Systems Mohsen A. Jafari Department of I ndu s trial EngineeringRutgers University


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