Performance optimisation for closed loop control strategies towards simplified model of a PMSM drive by comparing with different classical and fuzzy intelligent controllers
by Chiranjit Sain; Atanu Banerjee; Pabitra Kumar Biswas; Valentina Emilia Balas
International Journal of Automation and Control (IJAAC), Vol. 14, No. 4, 2020

Abstract: In this proposed work, a substantial comparative performance optimisation has been established between the PI, lead, lead-lag and fuzzy logic controllers towards the closed loop control strategies of a simplified permanent magnet synchronous motor (PMSM) drive. By the introduction of sinusoidal pulse width modulation (PWM) control strategy, it is expected that the nature of armature current would be nearly sinusoidal and generated torque ripples will be lesser. In this proposed structure of a PMSM drive, the speed reference has been incorporated with a speed controller to fortify that the exact speed of the proposed motor match with the base speed with null speed error. The overall structure of the PMSM drive is separated into two loop control structure, inner current loop and outer speed loop. All the necessary performance indices of the proposed PMSM drive system are tested in a MATLAB/Simulink environment. Moreover, the performance of a fuzzy logic speed controlled PMSM drive as compared to all classical controllers provides better dynamic as well as steady state performance with reduced torque ripples. Therefore, the entire performance of the proposed simplified PMSM drive in closed loop control strategy is executed and efficacy of controllers is resolved under various operating conditions. Hence, the superiority of intelligent speed controller (fuzzy logic controller) for this proposed PMSM drive model over all classical controllers is validated and optimised for high performance applications. Finally, an auto-tuning control strategy for the fuzzy intelligent speed controller is also proposed for optimal operation of the drive system.

Online publication date: Wed, 08-Jul-2020

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