【摘要】 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。更多还原

【Abstract】 It is often very difficult for current PID optimization methods to take account of system’s requirement for quickness, reliability and robustness. To solve this problem, a multi-objective optimization design method was proposed. Under the precondition of guaranteeing the robust performance of the system, the minimum of overshoot, rise time and setting time were taken as the sub-objectives. Then SPEA2 and PGA were combined to reach the final conclusion. This method can obtain uniformly distributed Pareto-optimal solutions and has good convergence and powerful optimization capability. The satisfactory solution is selected in Pareto optimum set according to the system’s requirement, which provides an effective tool for measuring the performance of quickness, reliability and robustness. The superiority and effectiveness of the proposed method are supported by simulation results.更多还原