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

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.

KEYWORDS:

• Automatic Voltage Regulator (AVR)
• Crow Search Algorithm (CSA)
• Distance and Levy-flight based Crow Search Algorithm (DLCSA)
• Fractional Order Controllers (FOC)
• Fractional-Order-Proportional-Derivative (FOPD)
• Fractional-Order-Proportional-Integral (FOPI)
• Fractional-Order-Proportional-Integral-Derivative (FOPID) Controller

Acknowledgements

The authors would like to thank the anonymous referees, Editor-in-chief and associate editors for their valuable time and suggestions for improvement of this work.

Additional information

Notes on contributors

Amrit Kaur Bhullar

Amrit Kaur received her BTech degree in instrumentation engineering in 2001, MTech in instrumentation engineering from Punjab University Chandigarh in 2005. She is currently an assistant professor at Punjabi University Patiala and also pursuing her PhD in electronics and communication. She is having more than 14 years of teaching experience. Her research interests include optimization, fuzzy, and neural networks. Email: [email protected]

Ranjit Kaur

Ranjit Kaur did her bachelor's degree from Punjabi University, Patiala, master's from Punjab Technical University, Jalandhar, and PhD from Punjabi University, Patiala. She is having over 21 years of teaching experience. She is presently working as professor in the Department of Electronics and Communication Engineering at Punjabi University, Patiala. Her research interests are digital signal processing and optimization techniques. She is a member of IEEE and a life member of ISTE. She has more than 70 research publications in reputed journals and conferences. Email: [email protected]

Swati Sondhi

Swati Sondhi received the BE degree in electronics & instrumentation engineering, from IET, MJP Rohilkhand University, Bareilly, India, ME in electronic instrumentation & control engineering from Thapar University, Patiala, and PhD in the area of control systems from Electrical Engineering Department, Indian Institute of Technology Roorkee, India. She is currently working as an assistant professor at Thapar Institute of Engineering and Technology, Patiala, Punjab, India. Corresponding author. Email: [email protected]