Optimization of Fractional Order Controllers for AVR System Using Distance and Levy-Flight Based Crow Search Algorithm

Abstract

ABSTRACT This paper proposes a Distance and Levy-flight based Crow Search Algorithm (DLCSA) for optimization of three Fractional-order controllers: Fractional Order Proportional-Integral-Derivative (FOPID), Fractional Order Proportional-Integral (FOPI) and Fractional Order Proportional-Derivative (FOPD) controllers. Novelties of the proposed method are fourfold; (a) distance-based Flight length (Dfl)to improve the convergence rate, (b) Levy-flight based evasion to improve the efficiency of the algorithm, (c)adaptive awareness probability(AP) to set a tradeoff between local and global search and (d) Fuzzy based adaptive objective function to adjust the solution weights automatically. With such adaptations, the new approach preserves solution diversity and improves the convergence to global optima. To demonstrate the effectiveness of the contributions, proposed methods: DLCSA-FOPID, DLCSA-FOPI, and DLCSA-FOPD are implemented on an Automatic Voltage Regulator system and results are compared with few other well-established techniques like Zeigler–Nichols (Z-N), Artificial Bee Colony (ABC) Optimization (ACO), Multi-Objective Extremal Optimization (MOEO), Genetic Algorithm (GA), Chaos Ant Swarm (CAS) algorithm, Real Coded Extremal Optimization (RCEO), etc. Further to investigate robustness of proposed methods, the results are obtained for set-point tracking, noise suppression, load disturbance rejection, control effort, and modeling errors. The results demonstrate the better performance of the proposed method as compared to other state of the art techniques.