基于微粒群优化和模拟退火的约束广义预测控制算法

石油化工高等学校学报 ›› 2010, Vol. 23 ›› Issue (2): 89-92.

基于微粒群优化和模拟退火的约束广义预测控制算法

付秋峰,肖军,李书臣,张勇强,刘威

辽宁石油化工大学信息与控制工程学院, 辽宁抚顺 113001

收稿日期:2009-09-28 出版日期:2010-06-25 发布日期:2010-06-25
作者简介:付秋峰(1980 -), 男, 河南汝南县, 在读硕士
基金资助:
辽宁省教育厅科学研究计划资助(2004D031)

Algorithm of Constrained Generalized Predictive Control Based on PSO-SA

School of Information and Control Engineering,Liaoning Shihua Univercity,Fushun Liaoning 113001,P.R.China

Received:2009-09-28 Published:2010-06-25 Online:2010-06-25

摘要/Abstract

摘要： 提出一种基于微粒群优化和模拟退火的约束广义预测控制算法, 将微粒群优化和模拟退火引入到广
义预测控制的滚动寻优过程中, 增强对约束边界的搜索能力, 并将约束条件构成约束违反度函数和适应度函数一起
判断最优解的优劣, 该算法可以有效地提高广义预测控制处理约束的能力。通过对一个工业对象的仿真, 验证了该
算法的可行性和有效性。

关键词: 广义预测控制 , 约束 , 微粒群优化 , 模拟退火

Abstract:

An algorithm of constrained generalized predictive control was proposed based on partical swarm optimization(PSO) and simulated annealing(SA).PSO and SA were used for iterrative optimization to enhance the search capabilities for constraint boundary. Meanwhile, a violation function was constructed by constraints. This function and fitness function determined the optimal solution better or not. Constraint handling performance of GPC can be effectively improved by this algorithm. Its feasibility and efectiveness are verified via simulation study for an industrial object．

Key words:

Generalized predictive control, , Constraint, , Particle swarm optimization, , Simulated annealing

付秋峰,肖军,李书臣,张勇强,刘威. 基于微粒群优化和模拟退火的约束广义预测控制算法[J]. 石油化工高等学校学报, 2010, 23(2): 89-92.

FU Qiu-feng, XIAO Jun, LI Shu-chen, ZHANG Yong-qiang,et al. Algorithm of Constrained Generalized Predictive Control Based on PSO-SA[J]. Journal of Petrochemical Universities, 2010, 23(2): 89-92.

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