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Control Of Unstable Bioreactor Using Fuzzy Tuned PI controller

Introduction

Steady state bioreactor can exhibit non linear behavior at certain changes of paraeter values!

For certain" a sall changes in the syste paraeter can effect the steady state condition of the

bioreactor! Therefore " it is advisable for bioreactor to operate at at unstable continuous

bioreactor #ith feedbac$ controller syste! %o#ever" conventional unstable continuous

bioreactor PI controller al#ays give unsatisfactory response for the nonlinear process of

bioreactor! In soe cases this" iplication can further effect the output easureent and

technically destabilize the other operating condition! Therefore fuzzy tuned PI& controller is

introduced to iprove the perforance of the unstable continuous bioreactor! Fuzzy tuner

responsible in controlling the response rate of PI controller in non linear process! Thus" overall

process response can be onitored and iproved!

Objectives

'! To iprove the conventional PI controller response by using fuzzy tuning

(! To copared the perforance of the conventional PI controller #ith fuzzy tuning PI

controller

Methods

'! The scheatic diagra of the fuzzy self tuning PI controller is setup as belo#!

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(! The velocity algorith of the PI controller is set #ith)

*! The proportional gain" +c is tuned by fuzzy logic to $eep the integral gain"+i becoe

constant ,+i- +c./I0

1! The proportional gain +c is noralized bet#een 2 and ' by using linear transforation

+c"ina and +c" axa- allo#able controller gain obtained fro stability analysis

3! Fuzzy control need e and e input to evaluate Kc using its rule based ,see table

'0

4! 5fter the value of Kc is deterined" the value of +cina and +caxa is calculated! The

negative sign indicates that if error increases the anipulative variable has to decrease!

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The axiu an iniu allo#able values of the controller paraeter +c is chosen

around the design values calculated as earlier for PI control!

Result from article

Based on the article" the perforance of the closed loop syste #hen sub6ected #ith the fuzzy

tuning of PI controller to ove fro the stable steady state to the unstable steady state is

sho#n in Fig! '!

Fro figure ' it can be seen that the overshoot is reduced and it settles faster! For a *27 step

change in the set point"the oscillations are reduced as sho#n in Fig! (!

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8ith (27 uncertainty in easureent delay "9" for a *27 step change in set point"fuzzy tuning

helps to stabilize the closed loop response #here the PI controller fails to stabilise! The response

for this case is sho#n in Fig! *!

For a (37 uncertainty in the oscillations are reduced and it settles faster as sho#n in Fig! 1!

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To su up" #e can say that fuzzy tuning iproves the robustness of the controller under process

uncertainties #hich is a a6or re:uireent for non;linear processes such as bioreactors #ith

uncertainties in process $inetics!