A balanced arithmetic optimiation algorithm for efficient control of automatic voltage regulator

This study takes into consideration the critical role of automatic voltage regulators (AVR) in electrical power systems and proposes a new control mechanism. The primary function of AVR devices is to maintain a stable and consistent output voltage in power systems, thereby preserving the performance and lifespan of connected devices. AVR devices play a vital role in mitigating power fluctuations and voltage deviations. However, to ensure the effective operation of AVR devices, the need for the right control mechanisms is paramount. Therefore, the development of the correct control methods and algorithms is crucial for the efficient operation of AVR systems and reducing the impact of power interruptions. This thesis suggests an improved control approach for AVR systems using a novel artificial intelligence optimization technique. In this context, an arithmetic optimization algorithm is balanced using elite opposition-based learning and pattern search techniques to design an RPIDD2 controller. The proposed control method has demonstrated superior performance in comparative analyses, presenting a new approach for a robust control mechanism in AVR systems.