摘要
通过采用改进的粒子群优化(PSO)算法对锅炉过热汽温中的PID参数进行优化,分析了传统过热汽温控制方案的不足,提高了整个系统的鲁棒性。该方法的应用使得过热汽温得到了良好的控制,提高了经济运行效益,同时也说明了改进的粒子群算法寻优简单,能够使控制系统获得较好的动态特性和很强的鲁棒性,易于并行化。仿真结果表明,该算法是一种效率很高的寻优方法,是PID参数优化的理想方法。
The improved particle swarm optimization（PSO） is a novel evolutionary algorithm occurring recently,which has good optimization effects on continuous functions.Through using PSO to optimize the PID parameters of main-steam temperature control,the disadvantages of traditional control are analyzed,and the robust performance of the whole system is improved.By applying this control system,main-steam temperature is well controlled and the economical benefit is improved,which illuminate that the improved particle swarm optimization algorithm is simple for optimizing,and the control system obtains steady dynamic performance and strong robustness,and easy to parallel.The simulation results show the high efficiency of the proposed optimal method,being an ideal method of PID parameter optimization.
出处
《电气传动自动化》
2011年第1期58-61,共4页
Electric Drive Automation
