Back-propagation neural network for nonlinear self-tuning adaptive control

A backpropagation neural network is applied to a nonlinear self-tuning tracking problem. Traditional self-tuning adaptive control techniques can only deal with linear systems or some special nonlinear systems. The emerging backpropagation neural networks have the capability to learn arbitrary nonlinearity and show great potential for adaptive control applications. A scheme for combining backpropagation neural networks with self-tuning adaptive control techniques is proposed. The control mechanism is analyzed. Simulation results show that the new self-tuning scheme can deal with a large unknown nonlinearity