Smith-Predictor Controller Design Using New Reduction Model

To improve the performance of PID controller of high order systems by model reduction, we proposed two model reduction methods. One, Original model with two point $({\angle}G(jw)=\;-{\pi}/2,\;-{\pi})$ in Nyquist curve used gradient base method and genetic algorithm. The other, Original model without two point$({\angle}G(jw)=\;-{\pi}/2,\;-{\pi})$in Nyquist curve used to add very small dead time. This method has annexed very small dead time on the base model for reduction, and we remove it after getting the reduced model, and , we improved Smith-predictor for a dead-time compensator using genetic algorithms. This method considered four points$({\angle}G(jw)=0,\;-\pi/2,\;-\pi,\;-3\pi/2)$ in the Nyquist curve to reduce steady state error between original and reduced model. It is shown that the proposed methods have more performance than the conventional method.

새로운 축소 모델을 이용한 Smith-Predictor 제어기 설계