Design of Optimal Auto-Tuning Fuzzy PID Controller in Applications to Bio-Reactors
Date Issued
2015
Date
2015
Author(s)
Lee, Pei-Jung
Abstract
Fuzzy PID controllers are useful in conducting the behavior of nonlinear industrial processes. However, the famous tuning methods used in traditional PID controllers are not applicable to the fuzzy PID controller. This thesis focuses on the design techniques of optimal auto-tuning fuzzy PID controllers for bioreactors. The bioreactor is essentially a nonlinear process with unstable states and long measurement delay. Closed-loop control of the bioreactor intends to maintain the state at an unstable position where the system is more productive. The proposed optimal auto-tuning fuzzy PID controller implements the adaptive optimal control algorithm to achieve optimization on the control parameters. Auto tuning aims at satisfying the necessary conditions of optimality stated by the minimum principle. The fuzzy PID controller includes sliding-mode control rules to stabilize the bioreactor for carrying out auto tuning. The severe measurement delay inherent in the bioreactor is cancelled by a Smith predictor. The overall design is investigated for effectiveness in a simulation system of bioreactor, and the results outperforms a PID-controlled bioreactor tuned by the particle swarm optimization algorithm.
Subjects
fuzzy PID controller
auto-tuning
bioreactor
Type
thesis
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