抄録
This paper presents a method of adaptive control for nonlinear systems using neural networks. The control input is given by the sum of the output of an adaptive controller and the output of the neural network. The neural network is used to compensate the nonlinerity of plant dynamics that is not taken into consideration in the usual adaptive control. The role of the neural network is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems. New parallel neural networks are proposed. The learning time required for convergence and the network size of each parallel neural network can be reduced when compared to conventional neural network based control systems.
