Design and implementation of DTC based on AFLC and PSO of a PMSM

• Published in: Mathematics and computers in simulation Vol. 167; pp. 340 - 355
• Main Authors: Mesloub, H., Benchouia, M.T., Boumaaraf, R., Goléa, A., Goléa, N., Becherif, M.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.01.2020
• Subjects: Adaptive fuzzy logic controller (AFLC); Direct torque control (DTC); Particle swarm optimized (PSO); Permanent magnet synchronous motor (PMSM); Practical validation; Direct torque control (DTC); Particle swarm optimized (PSO); Practical validation; Permanent magnet synchronous motor (PMSM); Adaptive fuzzy logic controller (AFLC)
• ISSN: 0378-4754; 1872-7166
• DOI: 10.1016/j.matcom.2018.04.010

Direct Torque Control (DTC) of the permanent magnets synchronous motor (PMSM) is receiving increasing attention due to important advantages, such as high performance and low dependence on motor parameters. Recently, intelligent approaches were proposed to improve the DTC performance, in particular the torque and the flux ripples reduction. In this paper, Adaptive Fuzzy Logic Control (AFLC) and Particle Swarm Optimization (PSO) based DTC schemes are developed as alternative approaches to classical DTC. The AFLC technique uses two fuzzy controllers; the first AFLC supervises the tuning of the conventional speed loop PI regulator, while the second AFLC replaces the conventional DTC comparators. The second technique uses the PSO to optimize the speed loop PI regulator. Simulation and experimental results illustrate that the proposed intelligent techniques can effectively reduce flux and torque ripples with better dynamic and steady-state performance.