A Systematic Approach for Developing Nonlinear Control Systems With Fuzzy Logic

Abstract

In this paper we present a method for systematically developing nonlinear control systems that provide superior performance to conventional linear control systems. The approach uses the results of linear analysis as a starting point for designing and optimizing a nonlinear control system. A linear equivalent fuzzy logic control system is constructed to give the same performance as the “best” linear control system. The fuzzy logic control system is subsequently modified to improve performance by making an optimal nonlinear system. The method is illustrated by designing a nonlinear fuzzy logic control system for a headbox used for papermaking. A discrete linear quadratic regulator (DLQR) is first designed for this system. A nonlinear fuzzy logic control system is subsequently developed from the DLQR controller. The performance of these two control systems is then compared.