An improved marine predators algorithm-tuned fractional-order PID controller for automatic voltage regulator system

• Main Authors: Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mok, Ren Hao
• Format: Article
• Language: English
• Published: MDPI 2023
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/38213/1/An%20Improved%20Marine%20Predators%20Algorithm-Tuned%20Fractional-order%20PID_FULL.pdf; http://umpir.ump.edu.my/id/eprint/38213/; https://doi.org/10.3390/fractalfract7070561; https://doi.org/10.3390/fractalfract7070561
• Institution: Universiti Malaysia Pahang

One of the most popular controllers for the automatic voltage regulator (AVR) in maintaining the voltage level of a synchronous generator is the fractional-order proportional–integral-derivative (FOPID) controller. Unfortunately, tuning the FOPID controller is challenging since there are five gains compared to the three gains of a conventional proportional–integral–derivative (PID) controller. Therefore, this research work presents a variant of the marine predators algorithm (MPA) for tuning the FOPID controller of the AVR system. Here, two modifications are applied to the existing MPA: the hybridization between MPA and the safe experimentation dynamics algorithm (SEDA) in the updating mechanism to solve the local optima issue, and the introduction of a tunable step size adaptive coefficient (CF) to improve the searching capability. The effectiveness of the proposed method in tuning the FOPID controller of the AVR system was assessed in terms of the convergence curve of the objective function, the statistical analysis of the objective function, Wilcoxon’s rank test, the step response analysis, stability analyses, and robustness analyses where the AVR system was subjected to noise, disturbance, and parameter uncertainties. We have shown that our proposed controller has improved the AVR system’s transient response and also produced about two times better results for objective function compared with other recent metaheuristic optimization-tuned FOPID controllers.