Controller design for automatic voltage regulator system using modified opposition-based weighted mean of vectors algorithm

This paper proposes a modified optimization technique to determine the parameters of a real proportional-integral-derivative plus second-order derivative (real PIDD2) controller adopted in an automatic voltage regulator (AVR). In this regard, a modified opposition learning (mOBL) based weighted mean of vectors (INFO) algorithm (mOBL-INFO) is proposed for the first time. The performance of the proposed algorithm was initially tested on several benchmark functions with unimodal, multimodal, and low-dimensional properties. The obtained results against test functions were compared with the original INFO algorithm as the latter has already been shown to present superior results against several recent and effective metaheuristic algorithms. The developed mOBL-INFO algorithm was then used to adjust a real PIDD2 controller for the AVR system. The performance of the proposed method was tested using several analyses such as transient response, stability, and robustness. The related analyses demonstrated good promise of the proposed method for AVR system control. Furthermore, previously reported 26 effective methods were also employed to assess the performance of the mOBL-INFO-based real PIDD2 controller for the AVR system. The obtained results demonstrated that the proposed method in this study has an excellent transient response performance for AVR system control.