Design of optimal PID controller using hybrid differential evolution and particle swarm optimization with an aging leader and challengers

• Propose a modified PSO-DV algorithm using aging mechanism.
• The algorithm is tested on 12 benchmark functions.
• The algorithm is used for determining the optimal parameters of PID controller.
• Comparisons with different evolutionary algorithms show that the algorithm is efficient and robust.

This paper presents a new algorithm designed to find the optimal parameters of PID controller. The proposed algorithm is based on hybridizing between differential evolution (DE) and Particle Swarm Optimization with an aging leader and challengers (ALC-PSO) algorithms. The proposed algorithm (ALC-PSODE) is tested on twelve benchmark functions to confirm its performance. It is found that it can get better solution quality, higher success rate in finding the solution and yields in avoiding unstable convergence. Also, ALC-PSODE is used to tune PID controller in three tanks liquid level system which is a typical nonlinear control system. Compared to different PSO variants, genetic algorithm (GA), differential evolution (DE) and Ziegler–Nichols method; the proposed algorithm achieve the best results with least standard deviation for different swarm size. These results show that ALC-PSODE is more robust and efficient while keeping fast convergence.

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