Sensorless speed control of induction motor drives using reinforcement learning and self-tuning simplified fuzzy logic controller

Mohd Shah, Nor Shahida and Abdullah, Qazwan and Farah, Nabil and Ahmed, Mustafa Sami and Talib, Md Hairul Nizam and Aydoğdu, Ömer and Al-Moliki, Yahya Mohammed Hameed and Ugurenver, Abbas and Al-Mekhalfi, Mohammed A.A. and Aihsan, Muhammad Zaid and Salh, Adeb (2024) Sensorless speed control of induction motor drives using reinforcement learning and self-tuning simplified fuzzy logic controller. IEEE Access, 12. pp. 136485-136501. ISSN 2169-3536

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Abstract

Fuzzy logic controls (FLCs) have emerged as a promising solution for speed regulation in induction motor (IM) drives, offering adaptability to non-linearities, parameter variations, and external disturbances. However, conventional FLCs with fixed parameters and a huge number of rules can limit adaptiveness and increase system complexity, leading to deteriorated performance and high computational requirements. Moreover, reliance on costly encoders in traditional sensor-based IM drives introduces measurement errors and contributes toward the overall cost. To tackle these challenges, this paper proposes an integrated sensorless IM drive with a simplified self-tuning FLC (ST-FLC) and data-driven reinforcement learning (RL) for speed estimation. By employing a simplified 9-rule FLC instead of an intensive 49-rule counterpart and integrating a simple self-tuning mechanism based on mathematical equations, adaptiveness is maintained while computational overhead is reduced. Furthermore, the adoption of RL-based sensorless speed estimation eliminates reliance on encoder data, offering a cost-effective and computationally efficient alternative. Unlike conventional sensorless methods, the proposed sensorless-RL approach is data-driven and does not rely on motor parameters, leveraging a pre-trained policy for efficient speed estimation. Validation through simulation and experimentation on the dSPACE DS1104 platform demonstrates the efficacy of the proposed ST-FLC Sim 9-rule with sensorless RL. The method showcases accurate speed estimation, with simulation results comparable to standard 49-rule FLC and superior experimental performance. Significant computational time reduction is achieved with the proposed approach, resulting in a notable improvement in experimental performance metrics. Specifically, reductions of 50.5%, 20.4%, 15%, and 14.9% in settling time, current ripples, torque ripples, and current harmonics, respectively, underscore the practical benefits of the proposed integrated ST-FLC Sim 9-rule with sensorless-RL IM drive system.

Item Type:	Article
Uncontrolled Keywords:	FLC, ST-FLC, Sensorless IM drives, RL, Simplified rules, Computation requirement
Divisions:	Faculty of Electrical Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	14 Mar 2025 16:17
Last Modified:	14 Mar 2025 16:17
URI:	http://eprints.utem.edu.my/id/eprint/28455
Statistic Details:	View Download Statistic

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