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针时积分时滞系统,基于PID的Smith预估器需要被控对象的精确数学模型,对于实际工业过程中难以建模和参数变化的被控对象,其鲁棒性差,控制性能也往往达不到期望的效果。模糊PID控制器因其鲁棒性强的优点,在工业界得到了广泛应用,但目前仍然缺乏充分的解析理论分析。针对这些现状,将可解析的模糊PID控制器引入Smith预估器以提高其鲁棒性,并从理论上证明了这种Fuzzy-Smith预估器的鲁棒性优于传统的基于PID控制器的Smith预估器。基于二阶积分时滞系统,结合模糊PID的滑模特性,采用李亚普洛夫稳定性理论,在理论上分析和证明了由于模糊PID控制器中非线性项的存在从而能补偿更多的不确定性,因此其鲁棒性更好。最后的仿真结果进一步证明了这点。
The integral system with time-delay and needle-based Smith predictor needs accurate mathematical model of the controlled object. For controlled objects that are difficult to model and change parameters in real industrial processes, the robustness is poor and the control performance often does not reach To the desired effect. Because of its robustness, fuzzy PID controller has been widely used in industry, but it still lacks sufficient theoretical analysis. In view of these current situations, the resolvable fuzzy PID controller is introduced into the Smith predictor to improve its robustness, and it is theoretically proved that the robustness of this Fuzzy-Smith predictor is better than the traditional PID controller Smith Predictor. Based on the second-order integral time-delay system and the sliding mode characteristics of fuzzy PID, the Lyapunov stability theory is used to theoretically analyze and prove that more uncertainties can be compensated due to the existence of nonlinear terms in the fuzzy PID controller So its robustness is better. The final simulation results further prove this point.