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现有的PID参数优化方法往往难以同时兼顾系统对快速性、稳定性与鲁棒性的要求,本文针对这一缺陷,提出了一种多目标PID优化设计方法——在满足系统的鲁棒性的前提下,以超调量、上升时间和调整时间最小作为多目标优化的子目标,并将强度Pareto进化算法(SPEA2)与并行遗传算法(PGA)相结合对其求解。该算法求得的Pareto最优解分布均匀、收敛速度快、寻优能力强,决策者可根据实际系统的要求在Pareto解集中选择最终的满意解,这为快速性、稳定性与鲁棒性的权衡分析提供了有效的工具。仿真结果表明设计方法的有效性和优越性。
Existing PID parameter optimization methods are often difficult to take into account the system requirements for fastness, stability and robustness. In view of this defect, this paper proposes a multi-objective PID optimization design method - to meet the system robustness The overshoot, rise time and minimum adjustment time are taken as the sub-goals of multi-objective optimization, and the intensity Pareto evolutionary algorithm (SPEA2) is combined with the parallel genetic algorithm (PGA) to solve the problem. The Pareto optimal solution obtained by this algorithm is distributed uniformly and has the advantages of fast convergence and strong searching ability. The decision maker can choose the final satisfactory solution in the Pareto solution set according to the requirements of the actual system, which is fast, robust and robust Trade-off analysis provides an effective tool. The simulation results show that the design method is effective and superior.