Fuzzy inverse incremental model as tracking controller for SISO systems

Abstract

The problems encountered in using a fuzzy logic-based single neuron controller (SNC) for the tracking control of nonlinear SISO systems are shown to be overcome by the use of a fuzzy inverse incremental model (FIIM) of the same process as the tracking controller. The proposed method of tracking control uses online tuning of the universe of discourse and online identification of the FIIM. Three different algorithms for the linguistic/fuzzy modeling of SISO systems are proposed. The comparative results of using these algorithms for the tracking control of some nonlinear systems are shown.<>