[1]彭勇,陈俞强.改进蛙跳算法的LQR控制器的优化设计[J].智能系统学报,2014,9(04):480-484.[doi:10.3969/j.issn.1673-4785.201305055]
 PENG Yong,CHEN Yuqiang.Optimal design of the LQR controller based on the improved shuffled frog-leaping algorithm[J].CAAI Transactions on Intelligent Systems,2014,9(04):480-484.[doi:10.3969/j.issn.1673-4785.201305055]
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改进蛙跳算法的LQR控制器的优化设计(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第9卷
期数:
2014年04期
页码:
480-484
栏目:
出版日期:
2014-08-25

文章信息/Info

Title:
Optimal design of the LQR controller based on the improved shuffled frog-leaping algorithm
作者:
彭勇1 陈俞强12
1. 东莞职业技术学院 计算机工程系, 广东 东莞 523808;
2. 广东工业大学 自动化学院, 广东 广州 510006
Author(s):
PENG Yong1 CHEN Yuqiang12
1. Department of Computer Engineering, Dongguan Polytechnic, Dongguan 523808, China;
2. Faculty of Automation, Guangdong University of Technology, Guangzhou 510006, China
关键词:
LQR控制器倒立摆改进蛙跳算法优化设计权矩阵
Keywords:
LQR controllerinverted pendulumimproved shuffled frog-leaping algorithmoptimal designweight matrices
分类号:
TP18
DOI:
10.3969/j.issn.1673-4785.201305055
摘要:
针对多变量、非线性、强耦合性的倒立摆系统, 运用牛顿-欧拉方法建立了倒立摆的数学模型, 然后对该模型分别进行LQR控制。在 LQR 控制中, 权矩阵 QR 的选取直接影响着结构的动力反应和控制力。在标准蛙跳算法对权矩阵 QR 进行优化的基础上, 通过采取新的最差青蛙跳跃策略能有效提高算法的全局搜索能力, 同时加入自适应跳跃因子以加快算法的收敛时间。仿真实验表明, 该算法能有效地获得最优的权矩阵 QR, 使LQR控制效果能够满足结构性能要求。
Abstract:
Based on the inverted pendulum system which is multi-variable, nonlinear and strong coupling, a mathematical model of the inverted pendulum is established by utilizing the Newton-Euler method, and then the LQR control is implemented for the model. The weighted matrices Q and R have a direct impact on the dynamic response and control of the single inverted pendulum. During optimization of the matrices Q and R through use of the standard shuffled frog-leaping algorithm, the new worst frog jumping strategy can effectively improve the global search ability of the algorithm and the adaptive jump factor can speed up the convergence. The simulation experiment shows that the improved shuffled frog-leaping algorithm can effectively obtain the optimal weight matrices Q and R; as a result, the effect of the LQR controller meets the performance requirements of the single inverted pendulum.

参考文献/References:

[1] 刘浩梅,张昌凡. 基于LQR的环形单级倒立摆稳定控制及实现[J]. 中南大学学报:自然科学版,2012,43(9): 3496-3501.LIU Haomei, ZHANG Changfan. Stability control and realization of single link rotary inverted pendulum on LQR controller[J]. Journal of Central South University: Science and Technology, 2012, 43(9): 3496-3501.
[2] 张白莉. 单级倒立摆控制系统的稳定性算法设计[J]. 现代电子技术, 2011, 34(3): 120-122.ZHANG Baili. Stability algorithm design of first-order inverted pendulum control system[J]. Modern Electronics Technique, 2011, 34(3): 120-122.
[3] XU X. Suboptimal LQR problem: controller uncertainty and static output feedback controller[C]//Proceedings of the 23nd Chinese Control Conference. Changsha, China, 2004: 25-32.
[4] 胡蓉,陶雪华.单级倒立摆的LQR控制和DMC控制Matlab仿真比较[J].工业控制计算机, 2011, 26(8): 38-40.HU Rong, TAO Xuehua. Comparison study of LQR control and DMC control on single inverted pendulum[J]. Industrial Control Computer, 2011, 26(8): 38-40.
[5] ALIREZA R V. A hybrid multi-objective shuffled frog-leaping algorithm for a mixed-model assembly line sequencing problem[J]. Computers and Industrial Engineering, 2007, 53(9): 642-666.
[6] 贺毅朝,曲文龙,许冀伟. 一种改进的混合蛙跳算法及其收敛性分析[J]. 计算机工程与应用, 2011, 47(22): 37-40.HE Yichao,QU Wenlong, XU Jiwei. Improved shuffled frog-leaping algorithm and its convergent analysis[J]. Computer Engineering and Applications, 2011, 47(22): 37-40.
[7] LI Yinghai, ZHOU Jianzhong, ZHANG Yongchuan, et al. Novel multi-objective shuffled frog leaping algorithm with application to reservoir flood control operation[J]. Journal of Water Resources Planning and Management, 2010, 136(4): 217-226.
[8] 张倩,杨耀权. 基于遗传算法的PID控制器参数优化方法研究[J].电力科学与工程, 2011, 27(11): 53-57.ZHANG Qian, YANG Yaoquan. PID controller parameters optimization method based on genetic algorithm[J]. Electric Power Science and Engineering, 2011, 27(11): 53-57.
[9] 应明峰,鞠全勇,高峰. 基于粒子群优化的PID控制器设计与应用[J].计算机仿真, 2011, 28(11): 283-287.YING Mingfeng, JU Quanyong, GAO Feng. Design and application of PID controller based on particle swarm optimization[J]. Computer Simulation, 2011, 28(11): 283-287.
[10] 葛宇,王学平,梁静.改进的混合蛙跳算法[J].计算机应用, 2012, 32(1): 234-237.GE Yu, WANG Xueping, LIANG Jing. Improved shuttled frog-leaping algorithm[J]. Journal of Computer Applications, 2012, 32(1): 234-237.

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备注/Memo

备注/Memo:
收稿日期:2013-05-17。
基金项目:国家自然科学基金资助项目(61106019)
作者简介:陈俞强,男,1980年生,副教授,主要研究方向为片上系统、普适计算,主持并参与省部级科技计划项目多项,发表学术论文25篇,其中被EI检索多篇。
通讯作者:彭勇,男,1976年生,副教授,主要研究方向为智能算法、网络安全,参与省部级科技计划项目多项,发表学术论文17篇,其中被EI检索多篇。E-mail:289593848@qq.com
更新日期/Last Update: 1900-01-01