期刊文献+

基于最小二乘支持向量机的结构地震响应时滞控制算法 被引量:2

Least squares support vector machine based time-delay control algorithm for reducing seismic responses of structures
下载PDF
导出
摘要 针对时滞会导致控制系统效果降低、控制性能恶化甚至系统不稳定,将线性二次型控制(Linear QuadraticRegulator,LQR)与最小二乘支持向量机(Least Squares Support Vector Machines,LSSVM)进行集成,提出时滞LSSVM-LQR智能控制算法。该算法采集结构状态响应数据后,将用LQR算法计算出的结构最优控制力输入到LSSVM中,以训练并回归预测出时滞后时刻的最优控制力;由作动器对结构提供控制。基于MATLAB平台编写计算程序,并用一幢三层框架结构进行数值验证。结果表明,LSSVM-LQR算法能有效降低时滞对结构控制系统的不利影响。 The existence of time-delay always lowers control effects of control systems, results in worse control performance and even causes system instability. Through integrating the least squares support vector machine (LSSVM) and the linear quadratic regulator (LQR), a new intelligent control algorithm, referred to as the time-delay LSSVM-LQR, was proposed. The algorithm includes the following four steps: acquiring the state-space response data of the structure; using the LQR algorithm to calculate the optimal control forces; inputting the force data to LSSVM for training and giving out the prediction of optimal forces after time-delay; providing the control on the structure with the help of actuators. Based on MATLAB, a program was compiled. Subsequently, the LSSVM algorithm was verified by using the example of a 3-storey frame structure. The results show that the LSSVM algorithm can effectively reduce the adverse impact of time-delay on the control system of structures.
出处 《振动与冲击》 EI CSCD 北大核心 2013年第9期165-172,共8页 Journal of Vibration and Shock
基金 湖南省教育厅资助项目(11C0549)
关键词 振动控制 主动控制 时滞 最小二乘支持向量机 线性二次型最优控制 地震 Algorithms   Earthquakes   MATLAB   System stability   Time delay   Vibration control
  • 相关文献

参考文献11

二级参考文献32

  • 1郑锋,程勉,高为炳.控制存在时滞的系统的变结构控制[J].控制与决策,1993,8(2):95-99. 被引量:11
  • 2岳东,刘永清.时滞系统变结构控制设计的新方法[J].控制与决策,1994,9(4):311-314. 被引量:5
  • 3郑锋,程勉,高为炳.一类时滞线性系统的变结构控制[J].自动化学报,1995,21(2):221-226. 被引量:15
  • 4高为炳.变结构控制的理论及设计方法[M].北京科学出版社,1998..
  • 5张毅.电站锅炉燃烧优化控制理论及应用研究[D].北京:清华大学,2006.
  • 6Smola A J, Scholkope B. A tutorial on support vector regression[J]. Statistics and Computing, 2004,14:199 - 222.
  • 7Zheng L G, Zhou H, Wang C L, et al. Combing support vector regression and ant colony optimization to reduce NOx emissions in coal fired utility boilers [J]. Energy and Fuels, 2008, 22: 1034-1040.
  • 8Vapnik V N. Statistical Learning Theory [M]. New York: J Wiley, 1998.
  • 9Vapnik V N. The Nature of Statistical Learning Theory [M].New York: Springer Verlag, 1999.
  • 10Basharkhah M A, Yao J T P. Reliability aspects of structural control[J]. Civ. Eng. Syst, 1984,1:224 - 229.

共引文献150

同被引文献16

引证文献2

二级引证文献4

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部