A time delay neural network for dynamical system control

A novel time delay neural network is proposed for dynamical system control. In this work, A continuous recurrent neural network with time delay neurons in hidden layer is constructed, and the novel training algorithm and control law independent of delay are developed based on Lyapunovpsilas stability approach. Using the proposed method, the control error converges to a range near the zero point and remains within the domain throughout the course of the execution. The usefulness and validity of the presented algorithm are examined by numerical experiments.