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Ant-lion optimizer algorithm based FOPID controller for speed control and torque ripple minimization of SRM drive system

机译:基于蚁群优化器算法的FOPID控制器,用于SRM驱动系统的速度控制和转矩脉动最小化

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This paper mainly proposes a speed and current control strategy to minimize torque ripple in Switched Reluctance Motor (SRM). The dynamic behavior of the SRM is analyzed in terms of the parameters such as the speed, current, inductance and torque. Based on the parameters, the motor speed is controlled and minimized the torque ripples. After that, the control signal is generated for controlling the speed of the SRM. Hence, this paper proposed an enhanced speed and current control with PWM mode to minimize the torque ripples. A recent optimization approach based current and torque control technique is proposed for regulating the speed of the SRM. Here, Ant-Lion Optimizer (ALO) algorithm based Fractional Order PID (FOPID) controller is utilized to analyze the speed and torque of SRM. To get the optimal results of FOPID controller, the gain parameters are optimized. The ALO algorithm is utilized to achieve the optimal gain parameter of the FOPID controller. Finally, the proposed technique is implemented in the Matlab/Simulink platform. The performance analysis of the proposed method is demonstrated and contrasted with the existing techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm techniques.
机译:本文主要提出一种速度和电流控制策略,以最小化开关磁阻电机(SRM)的转矩脉动。根据诸如速度,电流,电感和扭矩等参数来分析SRM的动态行为。基于这些参数,可以控制电动机速度并最大程度地减小转矩波动。之后,产生用于控制SRM的速度的控制信号。因此,本文提出了采用PWM模式的增强型速度和电流控制,以最大程度地减小转矩脉动。提出了一种基于电流和转矩控制技术的最新优化方法来调节SRM的速度。在这里,基于分数阶PID(FOPID)控制器的蚁狮优化器(ALO)算法用于分析SRM的速度和转矩。为了获得FOPID控制器的最佳结果,对增益参数进行了优化。 ALO算法用于实现FOPID控制器的最佳增益参数。最后,在Matlab / Simulink平台中实现了所提出的技术。证明了该方法的性能分析,并与遗传算法(GA)和粒子群优化(PSO)算法等现有技术进行了对比。

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