Tuning of PID Controller Using GA for Ball and Hoop System

Abstract

The PID controller is one of the control strategies having simple structure was understood by plant operator, which is comparatively easy to tune. Irrespective of the attractiveness, the tuning characteristic of PID controllers is a task for engineers and scientists. Numerous procedures for tuning PID-controllers are recommended such as: Ziegler Nichols tuning method auto-tuning, artificial intelligence and optimization techniques. Evolutionary optimization techniques (EOTs) as emergent techniques, an efficient GA-based tuning approach aiming at enhancing PID control for complex processes is proposed. The test and simulation results demonstrate that the GA-based proposed scheme is capable and can be used to overcome the flaws of traditional fixed gain controller. The main role of the article is to appraise the algorithm for tuning of PID-controller gains along with minimization of cost function and argue about the capability, computational efficiency of GA to solve the problems in control systems.

Optimal tuning of a PID controller using a wound healing algorithm based on the clonal selection principle

“…The process of adjusting PID controller parameters is considered an optimization problem. Particle swarm optimization and genetic algorithm have been proposed by Gaing (2004) and Maha (2016) to find optimal PID parameters. In this method, the optimization process was performed for criteria such as overshoot, settling time and rise time.…”