Output feedback control of nonlinear systems using RBF neural networks

S. Seshagiri, H.K. Khalil
2000 IEEE Transactions on Neural Networks  
An adaptive output feedback control scheme for the output tracking of a class of continuous-time nonlinear plants is presented. An RBF neural network is used to adaptively compensate for the plant nonlinearities. The network weights are adapted using a Lyapunov-based design. The method uses parameter projection, control saturation, and a high-gain observer to achieve semi-global uniform ultimate boundedness. The effectiveness of the proposed method is demonstrated through simulations. The
more » ... tions also show that by using adaptive control in conjunction with robust control, it is possible to tolerate larger approximation errors resulting from the use of lower order networks. Index Terms-Adaptive control, output feedback, RBF networks.
doi:10.1109/72.822511 pmid:18249740 fatcat:j6qadwsaszaipazmutvw76tkci