Adaptive PID controller based on Lyapunov function neural network for time delay temperature control

Temperature is an important control variable in industrial processes. In this paper, an adaptive PID control algorithm has been discussed to track the process temperature. The presented control algorithm employs Lyapunov function based artificial neural networks for online tuning of proportional, integral and derivative actions. This algorithm has been successfully tested on the laboratory temperature control process trainer. For comparative analysis, the results have been contrasted with the conventional PID scheme. The experimental findings show that improved and stable tracking is achieved with the proposed adaptive PID controller.