Neuromorphic self-tuning PID controller

Using the nonlinear mapping capability of neural networks (NNs) a tuning method of a proportional integral derivative (PID) controller based on a backpropagation (BP) method of multilayered NNs is derived. Simulated and experimental results show that the proposed method can identify the appropriate parameters of the PID controller when it is implemented to both linear and nonlinear plants.<>