基于多目标粒子群的非线性系统PID控制器设计  

PID control of nonlinear systems based on multi-objective particle swarm optimization

作　　者：伍思敏[1] 陈珺[1] 刘飞[1] 

机构地区：[1]江南大学自动化研究所轻工过程先进控制教育部重点实验室,江苏无锡214122

出　　处：《计算机工程与应用》2014年第23期69-72,81,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.NSFC61134007);江苏省基础研究计划(自然科学基金)(No.BK2012111);中央高校基本科研业务费专项资金资助(No.JUSRP111A40);江苏高等学校优秀科技创新团队;江苏高校优势学科建设工程资助项目

摘　　要：PID控制器自产生以来,一直是工业生产过程中应用最广泛、最成熟的控制器。随着控制品质的要求越来越高,综合考虑系统的准确性、稳定性、快速性等多个性能指标,基于改进的Pareto最优排序多目标粒子群算法,给出一个适用于一类非线性系统的PID控制器设计方法。采用经典的非线性倒立摆系统作为PID被控对象进行仿真,将超调量和调节时间两个目标作为多目标粒子群算法的目标,求出一组Pareto最优控制参数,通过跟踪控制得到精确稳定的控制效果。Since production, the PID controller has been widely used in industrial production processes, with easy imple-mentation and mature theoretical analysis. Along with the increasingly high demand for quality, this paper considers the accuracy, stability and rapid of the multiple system performance indicators at the same time and presents a PID optimiza-tion control system design for a class of nonlinear systems based on the Pareto optimal sequencing multi-objective particle swarm optimization. For simulation, a classic nonlinear inverted pendulum system is illustrated as objects of PID control. The overshoot and adjustment time are defined as the fitness functions of the multi-objective particle swarm optimization. The typical nonlinear inverted pendulum tracking control uses a set of Pareto optimal control parameters and the result tes-tifies that the tracking control is accuracy and stability.

关 键 词：多目标粒子群算法 比例-积分-微分(PID)控制 非线性系统 倒立摆控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]