ANN based adaptive controller tuned by RTRL algorithm for non-linear systems

The paper presents artificial neural network (ANN) based adaptive controller for nonlinear systems. A state feedback adaptive control algorithm using fully connected recurrent neural network is employed. The desired trajectory for the on-line training of the neural network is obtained from a reference model. The synaptic weights adaptation of the network is based on real time recurrent learning algorithm (RTRL). Since the synaptic weights are adjusted in real time, this novel method of controller design has potential applications in non-linear systems. Simulation results of the controller applied to a simple non-linear dynamic system demonstrate the effectiveness of the controller.