Baran Hekimoğlu^*

Energy Engineering, Vol.120, No.7, pp. 1515-1540, 2023, DOI:10.32604/ee.2023.029024 - 04 May 2023

Abstract Two novel improved variants of reptile search algorithm (RSA), RSA with opposition-based learning (ORSA) and hybrid ORSA with pattern search (ORSAPS), are proposed to determine the proportional, integral, and derivative (PID) controller parameters of an automatic voltage regulator (AVR) system using a novel objective function with augmented flexibility. In the proposed algorithms, the opposition-based learning technique improves the global search abilities of the original RSA algorithm, while the hybridization with the pattern search (PS) algorithm improves the local search abilities. Both algorithms are compared with the original RSA algorithm and have shown to be highly… More > Graphic Abstract

Ahmed Agwa^1,2,*, Salah Elsayed³, Mahrous Ahmed³

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 799-815, 2022, DOI:10.32604/iasc.2022.019887 - 22 September 2021

Abstract Automatic voltage regulators (AVRs) in electrical grids preserve the voltage at its nominal value. Regulating the parameters of proportional–integral–derivative (PID) controllers used for AVRs is a nonlinear optimization issue. The objective function is designed to minimize the settling time, rise time, and overshoot of step response of resultant voltage with subjugation to constraints of PID controller parameters. In this study, we suggest using an Archimedes optimization algorithm (AOA) to tune the parameters of the PID controllers for AVRs. In addition, using an AOA to optimize the parameters of a fractional-order PID (FOPID) controller and a… More >