Optimization of Fuzzy Control for Magnetorheological Damping Structures

Abstract

Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of a magnetorheological damping structure that adopts semiactive control. Fuzzy control is a relatively appropriate control method, but fuzzy control design is susceptible to human subjective experience, which will decrease the control effect. This paper proposes new fuzzy control rules based on a genetic algorithm (GA) and particle swarm optimization (PSO) and performs a numerical simulation for a three-layer reinforced concrete frame structure under conditions of an uncontrolled structure, fuzzy control, fuzzy control optimized by GA, fuzzy control optimized by PSO, and GA-optimized FLC control (GA-FLC) proposed by Ali and Ramaswamy (2008). The results show that (1) the fitness values of the convergence of the two types of optimized fuzzy control are close. The speed of the convergence of the fuzzy control optimized by PSO is faster than that of the fuzzy control optimized by GA, but its running speed is slower. (2) Comparing the acceleration and displacement of the structure under the conditions of three different seismic waves, the effect of the optimized fuzzy control is better than that of the human experience fuzzy control and GA-FLC.