Xie, Chunli; Shao, Cheng; Zhao, Dandan Self-adaptive control of nonlinear systems based on least squares support vector machines dynamic inversion. (Chinese. English summary) Zbl 1265.93139 J. Dalian Univ. Technol. 52, No. 1, 100-105 (2012). Summary: 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 online 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. MSC: 93C10 Nonlinear systems in control theory 93C40 Adaptive control/observation systems 68T05 Learning and adaptive systems in artificial intelligence Keywords:dynamic inversion; least squares support vector machines; nonlinear system; self-adaptive control PDFBibTeX XMLCite \textit{C. Xie} et al., J. Dalian Univ. Technol. 52, No. 1, 100--105 (2012; Zbl 1265.93139)