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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!
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