NEURAL NETWORK CONTROL FOR A CLASS OF NONLINEAR UNCERTAIN SYSTEMS

A adaptive neural network control scheme is proposed for a class of uncertain nonlinear system. The known dynamics are used to design a feedback controller that can ensure the stability of the nominal model. A neural network-based adaptive compensator is designed for compensation of the system uncertainties. This control scheme can ensure the output tracking error asymptotically convergence to zero.