Fuzzy Control Systems With Reduced Parametric Sensitivity Based on Simulated Annealing

This paper discusses the design of fuzzy control systems (FCSs) with a reduced parametric sensitivity using simulated-annealing (SA) algorithms. Four generic families of objective functions expressed as integral quadratic performance indexes, which depend on the control error and squared output sensitivity functions, are suggested. SA algorithms are employed to minimize the objective functions in the appropriately defined optimization problems. A design method for Takagi–Sugeno proportional–integral fuzzy controllers (PI-FCs) is proposed. The resulting PI-FCs are intended for a class of plants characterized by second-order linearized models with integral component. A case study dealing with the angular position control of a dc servo system is used as test bed to validate the proposed new controller design. Experimental results illustrate the FCS performance.