Air condition’s PID controller fine-tuning using artificial neural networks and genetic algorithms

Abstract

In this paper, a Proportional–Integral–Derivative (PID) controller is fine-tuned through the use of artificial neural networks and evolutionary algorithms. In particular, PID’s coefficients are adjusted on line using a multi-layer. In this paper, we used a feed forward multi-layer perceptron. There was one hidden layer, activation functions were sigmoid functions and weights of network were optimized using a genetic algorithm. The data for validation was derived from a desired results of system. In this paper, we used genetic algorithm, which is one type of evolutionary algorithm. The proposed methodology was evaluated against other well-known techniques of PID parameter tuning.