A tunable stabilizing loop-based automatic voltage regulation system for overshoot reduction

The profundity of the extant technical exploits on the design of controllers for automatic voltage regulation (AVR) systems is enormous. Several approaches that involve the deployment of a proportional integral derivative (PID) controller and its variants have proven to offer great plausibility. Despite the performance and simplicity of the PID controller on the AVR system, the existence of overshoots is inherent in the design, which is detrimental to the safety of power equipment. This paved the way for the introduction of a stabilizing loop on the AVR system to strategically minimize the oscillations due to overshoots. In general, most stabilizing loops are characterized by filter with preselected gains which are often arbitrarily selected and not intelligently incorporated into the existing AVR architecture. This paper presents an AVR system with a tunable stabilizing loop. The essence of this is to intelligently enhance the performance of the PID controller in terms of overshoot reduction and reduce the sensitivity of the system to variation of parameters in an optimal fashion. The optimality of the design is realized by deploying some metaheuristic algorithms (Snake Optimizer (SO), Gazelle Optimization Algorithm (GOA), Smell Agent Optimization (SAO), Pelican Optimization Algorithm (POA), Dandelion Optimization Algorithm (DOA) and American Zebra Optimization (AZOA)), on a set of well-posed constraints to deduce the best combination of values of the parameters of the PID and the adjustable gain of the stabilizing loop, while the integral time absolute error (ITAE) is used as the cost function. Comparative analyses of the performance of this design topology with that of a PID-based design without a stabilizing loop reveal that the proposed design offers a significant reduction in percentage overshoot. More so, the credibility and suitability of the smell agent optimization algorithm (SAO) and the pelican optimization algorithm (POA), among the deployed algorithms, in ascertaining zero overshoot were justified. Furthermore, the robustness analysis was made on the developed design to reveal and ascertain its level of insensitivity to parameter variation.