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基于粒子群算法混合优化的广义预测控制器研究
引用本文:肖本贤,朱志国,刘一福.基于粒子群算法混合优化的广义预测控制器研究[J].系统仿真学报,2007,19(4):820-824.
作者姓名:肖本贤  朱志国  刘一福
作者单位:1. 合肥工业大学自动化研究所,合肥,230009
2. 安徽省电力科学研究院,合肥,230022
摘    要:提出一种基于粒子群算法混合优化的广义预测控制器(generalized predictive control based on particleswarm optimization,简称PSOGPC),将粒子群优化算法(particle swarm optimization,简称PSO)引入到广义预测控制的滚动寻优过程中,有效解决了广义预测控制在被控对象存在约束时难以获得最优预测控制输入及求解复杂的问题。并对普通粒子群优化算法进行了改进,提高了优化过程的求解精度和收敛速度。多种约束情况和对电厂锅炉的主汽温控制系统的仿真结果表明了该方法的有效性和优良的控制性能。

关 键 词:广义预测控制  粒子群优化算法  混合优化策略  约束
文章编号:1004-731X(2007)04-0820-05
收稿时间:2005-12-08
修稿时间:2006-01-31

Research of Hybrid Optimized Generalized Predictive Controller Based on Particle Swarm Optimization
XIAO Ben-xian,ZHU Zhi-guo,LIU Yi-fu.Research of Hybrid Optimized Generalized Predictive Controller Based on Particle Swarm Optimization[J].Journal of System Simulation,2007,19(4):820-824.
Authors:XIAO Ben-xian  ZHU Zhi-guo  LIU Yi-fu
Institution:1.Institute of Industrial Automation, Hefei University of Technology, Hefei 230009, China; 2.Anhui Electric Power Research Institute, Hefei 230022, China
Abstract:A new hybrid optimized generalized predictive control(GPC) based on the PSO technique(PSOGPC) was proposed in which the PSO is used for iterative optimization.The method can solve the complicated solving equation problem when GPC is difficult to obtain the optimum prediction control input because of the constraint of the control process.Furthermore,PSO was modified here to improve the solving precision and convergent rates of optimization procedure.The multi example simulation results show the method's validity and superior control performance.
Keywords:generalized predictive control(GPC)  particle swarm optimization  hybrid optimization strategy  constraint
本文献已被 CNKI 维普 万方数据 等数据库收录!
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