Design of a recursive fuzzy controller with nonlinear fuzzy rule base

Defining a proper fuzzy rule base is the most difficult task in the design of fuzzy controllers. Because there are not much expert knowledge directly available for fuzzy controllers and analytical calculations with nonlinear fuzzy rule bases are very complicated, most fuzzy rule bases defined manually in the literature are linear. In this paper, we propose a recursive fuzzy controller that employs nonlinear fuzzy rules with constraints. The recursive structure and the constraints obtained from analytical calculations guarantee asymptotic stability of the fuzzy controller and the closed-loop system. By using multi-objective evolutionary algorithms for optimal tuning, the proposed controller shows superior performance over a fuzzy controller with linear fuzzy rule base and a conventional state-feedback controller.