Grey fuzzy sliding mode controller design with genetic algorithm

A grey fuzzy sliding mode controller with genetic algorithms (GA-GFSMC) is proposed. It employs the genetic algorithms, grey model, and sliding mode control techniques for designing the fuzzy controller. We first utilize the sliding mode control techniques to design the fuzzy control rules, so that the fuzzy sliding mode controller (FSMC) can be widely utilized in different control system. Then, we adopt a grey model as a predictor to make the one-step prediction into the future for the state behavior of the controlled plant. Thus we can obtain the control signals in advance based on the predicted values, and maintain the system safety limit. Finally, we apply the genetic algorithms to search the optimal set of parameters for the GFSMC, and hence to obtain the GA-GFSMC. Simulation results show that the GA-GFSMC can well control most of nonlinear systems without knowing their mathematical models, and it exhibits better performance than that of the GFSMC and FSMC