Otomatik gerilim regülatör sistemi için karşıt tabanlı atom arama optimizasyon algoritması

Abstract

 OBL strategy is used to improve the convergence of the ASO.  The performance of PIDD 2 controller is better than PID and FOPID controllers.  The proposed novel method is efficient and robust. Figure A. OBASO implementation block diagram for optimizing the AVR performance Purpose: This article presents a modified version of atom search optimization (ASO) algorithm that uses the opposition-based learning (OBL) to improve the search space exploration. Theory and Methods: OBL is a commonly used machine learning strategy for increasing the performance of meta-heuristic algorithms. As a new design method, the opposition-based ASO (OBASO) algorithm was proposed for the first time in determining the optimum values of the proportional-integral-derivative plus second order derivative (PIDD 2) controller parameters in an automatic voltage regulator (AVR) system. In the design problem, a new objective function, including the integral of time-weighted squared error (ITSE) and overshoot all together, was optimized with the proposed OBASO algorithm to find the best values of the PIDD 2 controller parameters. Results: The performance of the proposed OBASO tuned PIDD 2 (OBASO-PIDD 2) controller is compared to that of the classic ASO tuned PIDD 2 (ASO-PIDD 2) controller as well as the PID, fractional order PID (FOPID) and PIDD 2 controllers tuned with modern heuristic algorithms. Comparative transient and frequency response analyzes were conducted to assess the stability of the proposed approach. In addition, considering the possible changes in AVR parameters, the robustness of the proposed approach was tested. Conclusion: The extensive simulation results and comparisons with other existing controllers show that the proposed OBASO-PIDD 2 controller with a new objective function has a superior control performance and can highly improve the system robustness with respect to model uncertainties.

Maiden application of fractional order PID plus second order derivative controller in automatic voltage regulator

“…There are also studies in the literature involving PIDD 2 controllers. In this context, PSO, 7 improved whale optimization algorithm (IWOA), 18 and an opposition‐based atom search optimization (OBASO) 19 are utilized for determining the parameters of PIDD 2 controller of AVR system. It is seen that the number of studies on FOPID controllers is relatively higher than the studies on PIDD 2 .…”