Optimal design of automatic voltage regulation controller using hybrid simulated annealing - Manta ray foraging optimization algorithm

This paper presents a hybrid metaheuristic method for optimal tuning of four different types of proportional-integral-derivative (PID) controller for an automatic voltage regulator (AVR) system. The method is based on the manta ray foraging optimization algorithm which is merged with the simulated annealing algorithm. Additionally, novel objective functions for the optimization of the controller's parameters are proposed. The performance of the obtained ideal PID, real PID, fractional-order PID, and PID with second-order derivative controllers is verified by carrying out a comparison with the controllers tuned by different algorithms presented in the literature. Results of the simulations validate that each type of controller tuned with the proposed SA-MRFO algorithm outperforms the controllers tuned by other algorithms. Further, a comparative analysis is carried out to determine the most suitable controller for application in AVR systems. The main advantage of the proposed algorithm is the significant increase in the convergence speed. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-ncnd/4.0/).

Automated summary

The paper introduces a hybrid metaheuristic method for optimal tuning of PID controllers in AVR systems, where the performance of different types of PID controllers is compared through simulations, validating the superiority of the algorithm.