DESIGN AND DEVELOPMENT OF ANFIS WITH FOPID CONTROL SCHEME FOR BRUSHLESS DC MOTOR SPEED CONTROL

Mohammed Shameem Sultana1, Chekka Ravi Kumar2

Abstract

BLDC motors are ideal for low and medium power applications because to their high torque/inertia ratio, good dependability, huge energy density, broad speed control range, and low maintenance needs. It is a three-phase synchronous motor with rotor permanent magnets and stator three phase windings. Because there are no mechanical brushes or commutator assemblies, it is also known as a remotely switched motor. Instead, electronic commutation is employed depending on the position of the rotor measured by the Hall-effect position sensor. Modern speed control solutions for drives with different speeds have evolved significantly from their traditional equivalents. Closed loop control strategies were established for industrial drive applications, and PI, PID, FOPID, and FUZZY controllers were utilised in conjunction with power electronic converters. A Hybrid Fuzzy-FOPID controller is employed in the current system to regulate the BLDC motor. The DC inverter voltage is controlled by a fuzzy logic controller, and the BLDC motor set point is controlled by a FOPID controller via the inverter gate circuit. A modified harmony search (HS) metaheuristic Algorithm is designed for modifying FOPID controller settings. The motor is tested in three distinct working circumstances to confirm the functionality of the present controller: no-load function, varying load execution, and varying speed operation. The hybrid fuzzy-FOPID controller that was installed greatly enhances motor speed and torque responsiveness in a number of operating circumstances. In the current system, Hybrid Fuzzy-FOPID has the drawback of having a slightly greater steady-state error, ripples throughout the speed profile, and restricted starting torque in all three operating circumstances. To overcome the drawbacks of the present system, we must employ a BLDC motor with a hybrid ANFIS-FOPID controller. The proposed work was created and implemented in MATLAB/SIMULINK.

Keywords:

:Speed control, Brushless DC (BLDC) motor, Fuzzy control, ANFIS, FOPID, Harmony Search (HS).


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References


[1] M.A.Abido, M.A.M.Eltoum, “Hybrid fuzzy fractional order PID based speed control for brushless DC motor”, Arabian journal for science & engg, 2021. [2] Maharajan, M.P.; Xavier, S.A.E.: Design of Speed Control and Reduction of Torque Ripple Factor in BLdc Motor Using Spider Based Controller. IEEE Trans. Power Electron. 34(8), 7826–7837 (2019) [3] Baharudin, N.N.; Ayob, S.M.: “Brushless DC motor drive control using Single Input Fuzzy PI Controller (SIFPIC),” 2015 IEEE Conf. Energy Conversion, CENCON 2015, 13–18 (2015) [4] Potnuru, D.; Tummala, A.S.L.V.: Grey wolf optimization-based improved closed-loop speed control for a BLDC motor drive. Smart Innov. Syst. Technol. 104, 145–152 (2019) [5] Prabhu, P.; Urundady, V.: One-Cycle Controlled Bridgeless SEPIC with Coupled Inductors for PAM Control-Based BLDC Drive. Arab. J. Sci. Eng. 44(8), 6987–7001 (2019) [6] M. Yashoda and O. Chandra Sekhar, Design and Analysis of ANFIS based BLDC Motor.Indian Journal of Science and Technology, 9(35), (2016) [7] H. Lu, L. Zhang, and W. Qu, A New Torque Control Method for Torque Ripple Minimization of BLDC Motors With Un-Ideal Back EMF.IEEE Transactions on Power Electronics, 23(2),(2008). [8] H. Wu, M. Wen, and C. Wong, Speed Control of BLDC Motors Using Hall Effect Sensors Based on DSP.(2016) International Conference on System Science and Engineering (ICSSE), National Chi Nan University, Taiwan, July 7-9, 2016 [9] S. B. Ozturk and H. A. Toliyat, Direct Torque and Indirect Flux Control of Brushless DC Motor. IEEE/ASME Transactions on Mechatronics, 16(2), (2011), pp.351-360. [10] V. Bist, and B. Singh, PFC Cuk Converter Fed BLDC Motor Drive. IEEE Transactions on Power Electronics, [11] K.Meenendranath Reddy, G.Hussain Basha, Saggi Raj Kumar, V.Srikanth. An Efficient MPPT Technique using Fuzzy/P&O Controller for PV Applications. International Journal for Modern Trends in Science and Technology 2021, 7, pp. 106-111. https://doi.org/10.46501/IJMTST0710017 [12] R. Kumar and B. Singh. Single Stage Solar PV Fed Brushless DC Motor Driven Water Pump.IEEE Journal of Emerging and Selected Topics in Power Electronics [13] R. Kumar and B. Singh. Grid Interactive Solar PV Based Water Pumping Using BLDC Motor Drive. IEEE Transactions on Industry Applications [14] Balavenkata Muni, N., Sasikumar, S., Hussain, K., Reddy, K.M. (2022). A Progressive Approach of Designing and Analysis of Solar and Wind Stations Integrated with the Grid Connected Systems. In: Kalinathan, L., R., P., Kanmani, M., S., M. (eds) Computational Intelligence in Data Science. ICCIDS 2022. IFIP Advances in Information and Communication Technology, vol 654. Springer, Cham. https://doi.org/10.1007/978-3-031-16364-7_7. [14] Gobinath, S.; Madheswaran, M.: Deep perceptron neural network with fuzzy PID controller for speed control and stability analysis of BLDC motor. Soft. Comput. 24(13), 10161–10180 (2020)

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