Paper ID: 903

Improving Single-Phase Induction Motor Speed Control Using Model Reference Adaptive System And Fuzzy-Pid Regulator

Kurui Faith Jepchirchir^*, Muriithi Christopher Maina, & Oyie Nicholas

Murang’a University of Technology, Murang’a, 10200, Kenya

*Corresponding author: kuruifaith@gmail.com

 

Abstract

As industries strive to enhance their applications to meet growing market demand, accurate speed control of single-phase induction motors (SPIMs) remains a crucial concern. This paper presents the modelling and simulation of SPIM speed control based on a hybrid Model Reference Adaptive System (MRAS) integrated with a Fuzzy–PID regulator. Superior performance was achieved by integrating MRAS with a fuzzy-PID regulator using an adaptive self-tuning mechanism. The purpose of this integration was to leverage the adaptive nature of MRAS and the robustness of the Fuzzy-PID regulator to enhance performance and reliability in SPIM drives without the need for physical sensors. The SPIM speed was modelled using differential equations representing both electrical and mechanical dynamics. MRAS was implemented using motor voltage equations, with an adaptive model estimating the rotor speed. The Fuzzy-PID regulator optimized control performance by processing the error and its rate of change through a fuzzy controller, with the output fed into a PID controller to ensure error stabilization. A review of relevant literature on SPIM and associated control theories was conducted, and several journal papers were analyzed. Simulation of the proposed MRAS–Fuzzy-PID approach in MATLAB demonstrated that sensorless speed regulation considerably reduced rise time, enabling the motor to reach the desired speed quickly while eliminating steady-state error compared to systems without controllers. The results indicate that the rise time was reduced by 65.5%, the overshoot decreased by 58.9%, the steady-state error decreased by 71.8%, and the Integral of Absolute Error (IAE) was minimized. These improvements ensured stable operation under varying load conditions, with minimal fluctuations in speed. Integrating MRAS with a Fuzzy-PID controller further enhances the speed stability, robustness, and adaptability of SPIM drives.

Keywords: fuzzy-PID; model reference adaptive system (MRAS); sensorless SPIM; speed control.

References

Almahasneh, A. R., Al-Durra, A., & Al-Turjman, O. (n.d.). Hybrid fuzzy-PID speed control of a sensorless vector-controlled single-phase induction motor using a novel algorithm. IEEE Access, 8.

Bhinav, V., & Deshpande, A. (2021). Comparison of Fuzzy Logic Controller with PID Controller in Induction Motor Control. Asian Research Journal of Current Science, 3(1), 194-198.

Elattar, E. A., & Amer, M. H. (2018). Fuzzy logic control of single-phase induction motor for speed regulation. Ain Shams Engineering Journal, 9(1), 1-10.

Fikireselam, & Zerihun, M. (2022, September 02). Design and Simulation of Speed Sensorless Induction Motor Drive using FOBI Controller and ANN Estimator. Retrieved 02 28, 2023, from http://dspace.org

Fnaiech, M. A., Guzinski, J., Trabelsi, M., Abdellah, K., & Benbouzid, M. (17 April 2021). MRAS-Based Switching Linear Feedback Strategy for Sensorless Speed Control of Induction Motor Drives. Applications of Modern Methods to Control of Electric Drives, 14(11).

Hamdi, W., Hammoudi, M. Y., & Betka, A. (2023). Sensorless Speed Control of Induction Motor Using Model Reference Adaptive System and Deadbeat Regulator. Engineering Proceedings. Algeria.

Hussain, M. N., & Usman, K. M. (2021). An Optimal Fuzzy Logic-based PI Controller for the Speed Control of an Induction Motor using the V/F Method. Engineering, Technology & Applied Science Research, 11(4), 7399-7404.

Irianto, Murdianto, F. D., Sunarno, E., Proboningtyas, & Dewinta, D. (April 2021). Comparison Method of PI, PID and Fuzzy Logic Controller to Maintain Speed Stability in Single-Phase Induction Motors, 8(1), 7-16.

Manoj, V. (May 2016). Sensorless Control of Induction Motor Based on Model Reference Adaptive System (MRAS). International Journal for Research In Electronics & Electrical Engineering, 2(5), 5.

MathWorks. (n.d.). Induction Machine, Single-Phase. Retrieved from https://www.mathworks.com/help/sps/ref/inductionmachinesinglephase.html?searchHighlight=single+phase+induction+motor&s_tid=srchtitle_support_results_14_single%2520phase%2520induction%2520motor

Md Shah, F., & Paliwal, S. (2018). Speed Control of Three Phase Squirrel Cage Induction Motor Using Fuzzy Logic Controller. Journal of Engineering Research and Application, 8(5), 03-07.

Mohamed, A., El-Sehiemy, & A, R. (2019). Performance enhancement of asplit-phase Induction motor by using a fuzzy-based PID controller. Journal of Electrical Engineering, 70(2), 103–112.

Mugheri, N. H., & Keerio, M. U. (2021). An Optimal Fuzzy Logic-based PI Controller for the Speed Control of an Induction Motor using the V/F method. Engineering, Technology & Applied Science Research, 11(4), 7399-7404.

Soni, S. K., Khemariya, M., & Singh, A. (2022). Sensorless Speed Control of Induction Machine with Adaptive-Neuro Fuzzy Technique Integrated MRAS Module. International Journal of Engineering Trends and Technology, 70(7), 406.

Sujeet, K. S., Manish, K., & Anand, S. (2022). Sensorless Speed Control of Induction Machine with Adaptive-Neuro Fuzzy Technique Integrated MRAS Module. International Journal of Engineering Trends and Technology, 405-413.

Sumon, D., Sachin, J., & Vivek, A. (January 2019). RES and battery fed energy efficient singlephase induction motor drive system with retrofit solution. IET Electric Power Applications, 13(3), 332-339.

Tejeshree, J. B., & S, M. S. (2020). Analysis of Proportional Integral Controller and Fuzzy Logic Controller for Single Phase Induction Motor. International Journal of Innovative Technology and Exploring Engineering, 9(10), 2278-3075.

Zorgani, Y. A., Hajji, S., Koubaa, Y., & Boussak, M. (2023). Model Reference Adaptive System Scheme for Sensorless Induction Motor Drive.