Adaptive control for nonlinear multivariable systems using a dynamic recurrent neural networks and conventional linear controller

In this paper a real time control technique for a nonlinear multivariable system is presented. The proposed technique is a hybrid approach, which combines the ability of a dynamic recurrent neural network for modeling purposes and a linear control law to design the controller, providing a bridge between the field of neural mtworks and the well known linear adaptive control methods. In this paper, we consider that the state of the system is accessible. Simulation results are presented toward the end of the paper to show the effectiveness of the proposed methodology.