Novel Speed Sensorless DTC Design for a Five-Phase Induction Motor with an Intelligent Fractional Order Controller Based-MRAS Estimator

Sifelislam Guedida, B. tabbache, Khaled Mohammed Said Benzaoui, K. Nounou, Mokhtar Nesri
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Abstract

This paper presents a fractional-order adaptive mechanism-based model reference adaptive system (MRAS) configuration for speed estimation of sensorless direct torque control (DTC) of a five-phase induction motor. In effect, the fractional-order proportional-integral (FOPI) controller parameters are obtained by the particle swarm optimisation (PSO) algorithm to enhance the MRAS observer response. Thus, the developed algorithm in the speed loop control of the DTC strategy to increase its robustness against disturbances. Moreover, a comparative study has been done of the proposed MRAS-PSO/FOPI speed estimator with the conventional MRAS-proportional-integral (PI) and the PSO-based MRAS-PI. Simulation results have carried out of the different controllers used in the adaptation mechanism of the MRAS estimator, to show the performance and robustness of the proposed MRAS-PSO/FOPI algorithm in use.
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基于智能分数阶控制器-MRAS 估算器的五相感应电机新型无速度传感器 DTC 设计
本文提出了一种基于分数阶自适应机制的模型参考自适应系统(MRAS)配置,用于对五相感应电机的无传感器直接转矩控制(DTC)进行速度估计。实际上,分数阶比例积分(FOPI)控制器参数是通过粒子群优化(PSO)算法获得的,以增强 MRAS 观察器的响应。因此,在 DTC 策略的速度环控制中,所开发的算法增强了其对干扰的鲁棒性。此外,还对所提出的 MRAS-PSO/FOPI 速度估计器与传统的 MRAS-比例-积分(PI)和基于 PSO 的 MRAS-PI 进行了比较研究。对 MRAS 估计器适应机制中使用的不同控制器进行了仿真,以显示所建议的 MRAS-PSO/FOPI 算法的性能和鲁棒性。
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