基于PSO 与LMI 优化的非线性模型预测控制

辽宁石油化工大学学报 ›› 2007, Vol. 27 ›› Issue (1): 86-89.

基于PSO 与LMI 优化的非线性模型预测控制

苏成利¹, 刘晓琴¹, 李　平¹ , 王树青²

1. 辽宁石油化工大学信息与控制工程学院, 辽宁抚顺113001 ;
2. 工业控制技术国家重点实验室, 浙江大学先进控制研究所, 浙江杭州310027

收稿日期:2006-09-13 出版日期:2007-03-20 发布日期:2017-07-05
作者简介:苏成利(1977 - ), 男, 辽宁辽阳市, 讲师, 博士。

Nonlinear Model Predictive Control Based on PSO and LMI Optimizing Algorithm

1. School of In formation and Control Engineering , Liaoning University of Petroleum & Chemical Technology ,Fushun Liaoning 113001 , P. R. China;
2. National Laboratory o f I ndustrial Control Technology ,Institute o f Adv anced Process Control , Zhejiang University , Hangzhou Zhej iang 310027, P. R. China

Received:2006-09-13 Published:2007-03-20 Online:2017-07-05

摘要/Abstract

摘要： 将微粒群算法(PSO)与线性矩阵不等式(LM I)用于输入受限非线性预测控制器的设计, 提出了基于PSO 与LMI 联合优化的非线性预测控制算法。算法采用双模控制策略, 利用LMI 离线优化确定终端不变区域, 以扩大非线性优化的求解范围, 降低算法的保守性。利用PSO 在线优化求解非线性预测控制输入, 以避免求解非线性规划问题, 同时对算法的稳定性进行了分析。仿真结果表明了该算法是有效的、可行的。

关键词: 微粒群优化, 　线性矩阵不等式, 　非线性预测控制, 　双模控制, 　终端区域

Abstract:

Particle swarm optimization (PSO) and linear matrix inequality (LMI) were used for the design of input -const rained nonlinear predictive controller . A nonlinear predictive control algorithm based on PSO and LMI was proposed. The dual - mode control strategy was adopted in the algorithm. LMI was used for off - line optimization to determine a terminal invariant region to expend the solution extent of nonlinear optimization and decrease conservation degree of the algorithm ;PSO was used for on - line so lving nonlinear predictive control input to avoid so lvingno nlinearprog ramming problems. The stability of the algorithm was analyzed. Simulation results show that the algorithm is efficient and feasible.

Key words: 　Particle swarm optimization, , Linear matrix inequality, , No nlinear predictive control, , Dual - mode control, , Terminal invariant region

苏成利1,刘晓琴1,李　平1,王树青2. 基于PSO 与LMI 优化的非线性模型预测控制[J]. 辽宁石油化工大学学报, 2007, 27(1): 86-89.

S U Cheng - li, LIU Xiao - qin,et al. Nonlinear Model Predictive Control Based on PSO and LMI Optimizing Algorithm[J]. Journal of Liaoning Petrochemical University, 2007, 27(1): 86-89.

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