摘要
提出基于最小二乘支持向量机动态逆的一种非线性系统自适应控制方法.该方法采用最小二乘支持向量机辨识非线性系统的动态逆模型,并将其串联在原系统之前得到复合的伪线性系统.对于建模误差、不确定因素等引起的非线性系统逆误差,采用在线最小二乘支持向量机进行自适应补偿.最小二乘支持向量机的在线参数调整规律由Lyapunov稳定性理论导出,并证明了非线性闭环系统的稳定性.仿真结果证明了该方法的有效性.
A method of self-adaptive control for nonlinear systems based on least squares support vector machines（LS-SVM） dynamic inversion is presented.The method cascades the dynamic inversion model approximated by LS-SVM with the original system to get the composite pseudo-linear system.The on-line learning while controlling LS-SVM is used to self-adaptively compensate the inversion error of nonlinear systems which may be due to modeling uncertainties and disturbances.The updating rule of LS-SVM weights is derived from Lyapunov stability theory,and the stability of the designed system is proved.Simulation results demonstrate the effectiveness of the proposed method.
出处
《大连理工大学学报》
EI
CAS
CSCD
北大核心
2012年第1期100-105,共6页
Journal of Dalian University of Technology
基金
国家自然科学基金资助项目(61074020)
中央高校基本科研业务费专项资金资助项目(DC10040101)
关键词
动态逆
最小二乘支持向量机
非线性
自适应控制
dynamic inversion
least squares support vector machines
nonlinear
self-adaptive control
