Multivariable Adaptive Lyapunov Fuzzy Controller for pH Neutralisation Process

A multivariable fuzzy logic controller with Lyapunov adaptive control scheme has been developed for a pH neutralisation process. In this study, the nominal neutralisation process condition exhibit nonlinear dynamics and multi-delayed-effects input variables. The proposed controller uses a Takagi-Sugeno fuzzy inference system and it has been optimised by genetic algorithm which minimizing the closed loop error in feedback control system. The optimised structure is used to predict three-difference control action simultaneously. The Lyapunov function is integrated in the fuzzy inference calculation at output membership function. The proposed controller has been tested and compared in several cases such as for set-point tracking, model plant mismatch and unknown disturbance. The adaptive fuzzy controller demonstrate better performance over the conventional PID controller in all the tested cases.