Analysis of Fuzzy-Smith Predictor for Integrating Plus Dead-time Plants

For integrating plus dead-time plants,the PID-based Smith predictor needs an accurate model.But in industrial processes, it is very difficult to obtain the accurate model and the parameters often change,so it results in poor robustness and control performance for the PID-based smith predictor.Although fuzzy PID controller has been widely used in industrial processes to its good robustness,the sufficient analytical theories are still lack.Thus,an analytical fuzzy PID controller is introduced to the Smith predictor in order to improve the robustness,and it can be proofed that the robustness of the Fuzzy-Smith predictor is better than the PID-based Smith predictor. After obtain the second order integrating plus dead-time model of the plant,based on Lyapunov theory and sliding mode control,it can be proofed that the nonlinear term can compensate more uncertainty and the robustness of the Fuzzy-Smith predictor is better.The simulation results further demonstrate it.