Adaptive output feedback tracking control for a class of uncertain nonlinear systems using neural networks.
This correspondence addresses the problem of designing robust tracking control for a class of uncertain nonlinear MIMO second-order systems. An adaptive neural-network-based output feedback tracking controller is constructed such that all the states and signals involved are uniformly bounded and the tracking error is uniformly ultimately bounded. Only the output measurement is required for feedback. The implementation of the neural network basis functions depends only on the desired reference trajectory. Therefore, the intelligent adaptive output feedback controller developed here possesses the properties of computational simplicity and easy implementation. A simulation example of controlling mass-spring-damper mechanical systems is made to confirm the effectiveness and performance of the developed control scheme.
Chang
Yeong-Chan
YC
Yen
Hui-Min
HM
D000465:Algorithms; D003198:Computer Simulation; D005246:Feedback; D015233:Models, Statistical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics