An improved RUN optimizer based real PID plus second-order derivative controller design as a novel method to enhance transient response and robustness of an automatic voltage regulator

Abstract

It is crucial to maintain the terminal voltage of a power network in order to reach a desired power quality. In this regard, a system called automatic voltage regulator (AVR) holds a significant role as it allows the adjustment of the terminal voltage. However, an AVR system requires an efficient control technique in order to provide stability. Considering this requirement, a new method is presented in this paper for transient response enhancement and robustness of the automatic voltage regulator (AVR) system. In that sense, the structure of a recently developed metaheuristic algorithm named Runge Kutta optimizer (RUN) is improved. The improved RUN (iRUN) optimizer is obtained by integrating the pattern search (PS) method into the original form of the RUN optimizer. The constructed iRUN optimizer is proposed as an efficient tool to tune a real proportional-integral-derivative (PID) plus second-order derivative (PIDD2) controller employed in an AVR system. In the proposed control mechanism, a performance index known as ZLG is used as an objective function. The proposed iRUN optimizer based real PIDD2 controller is comparatively demonstrated to be superior in terms of transient response and robustness against other available and recently reported methods based on PID, PID with filter (PID-F), PID acceleration (PIDA), fractional order PID (FOPID) and PID plus second-order derivative (PIDD2) controllers that are respectively tuned with metaheuristic optimizers of stochastic fractal search algorithm, Archimedes optimization algorithm, whale optimization algorithm, Henry gas solubility optimization and particle swarm optimization. The proposed method is shown to achieve no overshot and less rise and settling times compared to listed methods. It is also shown to be sufficiently robust in case of potential variations that may occur in the parameters of the system. The superiority is further demonstrated using thirty good performing and recently reported different methods that adopt different controllers and metaheuristic optimizers, as well. All comparative analyses confirm the excellent capability of the proposed iRUN optimizer based real PIDD2 controller for the AVR system control.