[1]刘 胜,? 宋 佳,?? 李高云.PSO并行优化LSSVR非线性黑箱模型辨识[J].智能系统学报,2010,5(1):51-56.
LIU Sheng,SONG Jia,LI Gao-yun.Modeling a complex nonlinear system with particle swarm optimizationand paralleloptimized least squares support vector regression[J].CAAI Transactions on Intelligent Systems,2010,5(1):51-56.
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LIU Sheng,SONG Jia,LI Gao-yun.Modeling a complex nonlinear system with particle swarm optimizationand paralleloptimized least squares support vector regression[J].CAAI Transactions on Intelligent Systems,2010,5(1):51-56.
PSO并行优化LSSVR非线性黑箱模型辨识
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
5
期数:
2010年第1期
页码:
51-56
栏目:
学术论文—人工智能基础
出版日期:
2010-02-25
- Title:
- Modeling a complex nonlinear system with particle swarm optimizationand paralleloptimized least squares support vector regression
- 文章编号:
- 1673-4785(2010)01-0051-06
- 关键词:
- 粒子群算法; 最小二乘支持向量机回归; 非线性系统辨识; 黑箱模型; 船舶操纵模型
- Keywords:
- particle swarm optimization; least squares support vector regression; nonlinear system identification; black box model; ship maneuvering
- 分类号:
- N945.1；TP18
- 文献标志码:
- A
- 摘要:
- 针对非线性黑箱系统辨识中存在不确定性、高阶次，采用常规辨识方法建立其精确数学模型十分困难等问题，提出一种基于自适应粒子群算法的最小二乘支持向量机回归(PSOLSSVR)非线性系统辨识方法.该方法采用2组自适应粒子群算法并行计算模型，分别利用自适应粒子群算法对LSSVR中的参数进行自动选取和矩阵迭代求解，既克服了传统LSSVR参数难以确定的缺点，提高了辨识精度，同时避免了复杂矩阵求逆运算，加快了计算速度.将该方法应用于船舶操纵性模型非线性系统辨识，仿真结果表明，由该方法得到的LSSVR能够有效地对系统进行建模，仿真精度高，结构简单，具有一定的理论推广意义.
- Abstract:
- Complex nonlinear systems usually suffer from highorder nonlinearity and uncertainty of parameters. This makes it difficult to establish an accurate mathematical model using conventional identification methods. To solve this problem, a new least squares support vector regression based on particle swarm optimization (PSOLSSVR) was proposed. This identification model used two PSOs in parallel. One automatically sets the parameters of the LSSVR, while the other iterates the matrix. Thus the precision of identification is ensured, and calculation speed is improved by avoiding matrix inversion. This method was employed in dynamic identification of ship steering. Simulations proved that the PSOLSSVR has a simple structure, high precision of model identification.
- 参考文献/References:
-
［1］LUO Weilin,ZOU Zaojian. Identification of response models of ship maneuvering motion using support vector machines［J］.Journal of Ship Mechanics, 2007(11): 832838.
［2］SUYKENS J A K, VAN GESTEL T, DE BRABANTER J， et al. Least squares support vector machines［M］.Singapore: World Scientific, 2002: 8092.
［3］GOETHALS I, PELCKMANS K. Identification of MIMO hammerstein models using least squares support vector machines［J］. Automatica, 2005, 41(7): 12631272.
［4］SUYKENS J A K, VANDEWALLE J. Least squares support vector machine classifiers［J］. Neural Processing Letters, 1999, 9(3): 293300.
［5］LIU Sheng, LI Yanyan. Application of compound controller based on fuzzy control and support vector machine on ship boilerturbine coordinated control system［C］//The 2007 IEEE International Conference on Mechatronics and Automation. Harbin, China, 2007: 97102.
?［6］刘 胜，李妍妍.自适应GASVM参数选择算法研究［J］.哈尔滨工程大学学报，2007，28（4）：398402.
LIU Sheng, LI Yanyan. Parameter selection algorithm for support vector machines based on adaptive genetic algorithm［J］. Journal of Harbin Engineering University， 2007， 28(4)： 398402.
［7］XIA Kewen，DONG Yao,DU Hongbin. Oil layer recognition model of LSSVM based on improved PSO algorithm［J］.Control and Decision, 2007(12): 13851389.
［8］LI Yonggang，GUI Weihua，YANG Chunhua，CHEN Zhisheng. A resilient particle swarm optimization algorithm ［J］. Control and Decision, 2008， 23 (1): 9598.
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备注/Memo
收稿日期：2009-03-01.
基金项目：
黑龙江省自然科学基金资助项目（A200419）.
通信作者：刘 胜.E-mail:liu.sch@163.com.
作者简介：
刘 胜，男，1957年生，教授，博士生导师，黑龙江省教学名师，黑龙江省重点一级学科“控制科学与工程”学科负责人.兼任教育部工程研究中心“船舶控制工程研究中心”主任，中国造船学会仪器仪表学术委员会副主任，黑龙江省自动化学会副理事长.主要研究方向为智能控制、鲁棒控制、船舶航行与姿态控制.目前承担国家“973”计划项目、国防基础研究基金项目、国防预研项目4项，省部级项目6项.曾获黑龙江省优秀教学工作者，中国船舶工业总公司优秀青年科技工作者，获省部级科学技术奖7项，省教学成果奖一等奖2项、二等奖2项，省教育科学研究成果一等奖4项，省部级自然科学技术学术成果奖8项.发表学术论文150余篇，被SCI、EI、ISTP检索70余篇，出版学术著作3部.
宋 佳，女，1983年生，博士研究生，主要研究方向为智能控制、船舶姿态控制.参与科研项目2项，发表学术论文10余篇，被EI、ISTP检索6篇.
?李高云，男，1981年生，博士研究生，主要研究方向为智能控制、故障诊断与容错控制、船舶航行与姿态控制.参与科研项目3项，获黑龙江省科学技术二等奖1项，黑龙江省高校科学技术一等奖1项.发表学术论文近10篇，被EI、ISTP检索4篇.
更新日期/Last Update:
2010-03-31