Metaheuristic-Assisted Advanced Control Approach for Time Delayed Unstable Automatic Voltage Regulator

Abstract

This work proposes a two-degree-of-freedom factional order proportional-integral-derivative (2-DOF FOPID) controller for automatic voltage regulator (AVR) to mitigate the impact of voltage transients and set-point variations in any power system network. An inherent communication time delay is considered in the investigated AVR plant. This inherent time delay occurs due to the presence of amplifier, exciter, generator, and sensor, making the system unstable. Such an unstable AVR system is still unexplored and difficult to control. The suggested control structure of the 2-DOF FOPID is flexible enough from the perspective of tuning and provides enhanced performance of an AVR system at the cost of a large number of controller design parameters. Therefore, the proposed controller is optimized by an advanced meta-heuristic technique; squirrel search algorithm (SSA) which leads to SSA tuned 2-DOF fractional order PID (S2DFPID) controller. Moreover, selecting an appropriate meta-heuristic approach is a very tedious task for such unstable systems and advanced control architecture. Hence, a systematic statistical approach is also employed to select an optimization technique for the specified purpose, and a rigorous comparative assessment of seven state-of-the-art optimization techniques is also presented in this work. Investigation reveals the superior performance of S2DFPID controller compared to SSA-tuned fractional order PID (SFPID), and SSA-tuned traditional PID (SPID) controllers in the presence of set-point variations, external load disturbances and parametric uncertainties.

Keywords:

• automatic voltage regulator
• power system network
• 2-DOF FOPID controller
• optimization

Additional information

Notes on contributors

Pawan Kumar Pathak

Pawan Kumar Pathak received the Ph.D. degree in Electrical Engineering from Banasthali Vidyapith, Rajasthan, India in 2021. He is currently working as an Assistant Professor in the School of Automation at Banasthali Vidyapith (Rajasthan, India). He has more than 7-years of teaching and research experience and published more than 20 research papers in Journals and Conferences of repute. His research interests include renewable energy, load frequency control, battery charger, electric vehicles, cyber-physical power systems, intelligent control, and meta-heuristics.

Mohit Jain

Mohit Jain is working as an Assistant Professor in School of Automation, Banasthali Vidyapith, Jaipur, India. He received his B. Tech. in Electronics and Instrumentation from U. P. Technical University, Lucknow, India in 2009. He received M. Tech. degree in Process Control in 2013 and Ph.D. degree in 2020 in the field of Instrumentation and control from the Netaji Subhas Institute of Technology, University of Delhi, India. He has published several research papers in international journals and conferences. He is a reviewer of many international journals and having more than 10 years of teaching as well as research experience. His main research interests include intelligent control systems, artificial intelligence and optimization algorithms. He is highly active in developing novel nature inspired optimization algorithms for real time systems.

Anil Kumar Yadav

Anil Kumar Yadav received the Ph.D. degree in Instrumentation and Control Engineering from the University of Delhi, Delhi, India in 2017. He is currently working as an Assistant Professor in the Department of Instrumentation and Control Engineering, Dr. B. R. Ambedkar NIT Jalandhar, Jalandhar (Punjab), India. He has 14 years of teaching and research experience and published more than 70 research papers in Journals and Conferences of repute. His research interests include renewable energy, hybrid systems, and nonlinear and intelligent control.