Neurodynamic Programming Approach for the PID Controller Adaptation

In this paper it is proposed a novel procedure for adaptive PID controller tuning applying Approximate Dynamic Programming. This procedure approximately solves the Bellman Equation for an optimum control design using an Actor-Critic scheme. An Artificial Neural Network is employed as a Critic to estimate the gradient of cost-to-go function. The PID Controller works as the Actor. This controller is commonly employed in a large number of industrial process. The method is applicable to optimal tuning in nonlinear control problems. Examples illustrate the effectiveness of the design scheme.