Design of self tuning fuzzy controllers for nonlinear systems

Nonlinearities present in the systems make their controller design a non-trivial task. The difficulty further increases in case of multi-input–multi-output (MIMO) systems with increased number of variables and interactions between them. In this paper, fuzzy based intelligent control schemes are designed for control of nonlinear single-input–single-output (SISO) and MIMO systems. The comparative study of the designed self tuning fuzzy controller with a standard Takagi–Sugeno (TS) fuzzy controller is discussed with application to a shell and tube heat exchanger (nonlinear SISO system) and a coupled two tank system (nonlinear MIMO system). Online tuning of the membership functions and control rules of fuzzy controller is carried out using simulated annealing (SA) to obtain improved performance by minimizing the error function. Experimental results demonstrate the effectiveness of the control scheme.