A novel excitation controller using support vector machines and approximate models
Xiaofang YUAN
Yaonan WANG
Shutao LI
摘要：This paper proposes a novel excitation controller using suppon vector machines(SVM)and approximate models.The nonlinear control law is derived directly based on an input-output approximation method via Taylor expansion,which not only avoids complex control development and intensive computation,but also avoids online learning or adjust.ment.Only a general SVM modelling technique is involved in both model identification and controller implementation.The robustness of the stability is rigorously established using the Lyapunov method.Several simulations demonstrate the effectiveness of the proposed excitation controller.
机标关键词：nonlinear control lawmodel identificationapproximation methodTaylor expansiononline learningLyapunov method
资助基金：the National Natural Science Foundation of China(60375001)the National Natural Science Foundation of China(60775047)the National Natural Science Foundation of China(60402024)
论文发表日期：2008-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：7( 239-245 )
英文信息