改进的PSO算法及其在控制系统参数整定中的应用(英文)

针对传统PID控制对非线性、强耦合控制系统的控制效果不佳,参数整定难度大的情况,基于改进的PSO算法,设计了一种HSIC控制器。该设计借助改进的粒子群算法对控制器参数整定进行了优化研究,基于粒子群算法,借鉴遗传算法中操作因子特性,提出了一种具有遗传思想的改进粒子群算法。在Matlab环境下,通过对标准函数的仿真实验测试,验证了该改进算法的优越性。利用Simulink工具对所设计的2种控制器进行了仿真比较研究,仿真实验表明,所设计的仿人智能控制器具有较好的控制品质,有比较好的可实现性。研究表明,整定后的控制器可以满足受控系统的控制品质要求。

Improved Algorithm of PSO and Its Application in Parameter Tuning of Control System

Hydromechatronics engineering is a complex system, and the control algorithm and parameter of control system directly influence the control quality of system. Aimed at the puzzle that the control effect of conventional PID controller is not as good as expected for the control system with nonlinearity and strong coupling, and it is very difficult to tune the parameters, this paper designed a sort of improved controller of human simulated intelligence based on the improved algorithm of PSO. By means of improved particle swarm optimization algorithm, this paper conducted the research on parameter tuning of controller, drew lessons from operation factor characteristic in genetic algorithm based on particle swarm optimization, and presented a sort of improved particle swarm optimization algorithm with genetic thought. Under the condition of Matlab environment, the simulation experiment has been conducted and the superiority of this improved algorithm has been validated. By using Simulink tool, two sorts of controller have been designed and the comparative simulations have been performed. The simulation results demonstrated that the designed human simulated intelligent controller have better control quality than other controllers and this controller is feasible. The research results show that the controller after parameter tuning can satisfy the demand of control quality in controlled system.