基于参数稳定空间的PID控制器设计

一阶加纯延时模型难以精确描述被控对象,因此传统的PID控制器不能取得满意的控制效果。基于精确的高阶模型提出了一种最优PID控制器的设计方法。利用广义Hermite-Biehler定理获得使闭环系统稳定的PID控制器集合。在该PID控制器集合中,运用遗传算法寻找基于ITAE指标最优的PID控制器参数。利用广义Kharitonov定理及Monte-Carlo随机试验方法对PID控制器鲁棒性和性能鲁棒性进行评价。仿真结果表明:该文算法对高阶对象具有良好的控制性能,对模型的不确定因素具有较好的适应性和鲁棒性。从而证实了该文算法的有效性,可以应用于高阶系统的控制。

Tuning PID controllers based on stable region

First-order time-delay models do not accurately describe industrial processes, so traditional PID controllers cannot provide satisfactory control. An optimized PID controller was developed using an accurate high-order system. A group of such PID controllers for stabilizing closed systems were designed using the generalized Hermite-Biehler theorem. The genetic algorithm was used to tune a PID controller with the optimal integrated time absolute error (ITAE) criterion from this group of PID controllers. The robust stability and performance of the PID controllers were evaluated using the generalized Kharitonov theorem and Monte-Carlo stochastic methods. The results show that the proposed method can effectively control this class of higher-order systems and is robust against modeling uncertainties. The simulation results substantiated the effectiveness of the proposed method for the control of higher-order systems.