永磁无刷直流电动机速度控制的粒子群优化PID控制器的设计与实现

M. Ramya, S. Jadhav, S. Pawar
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引用次数: 7

摘要

本文利用LabVIEW设计并实现了基于粒子群优化(PSO)的永磁无刷直流(PMBLDC)电机调速PID控制器。永磁无刷直流电机广泛应用于航空、机器人、医疗、食品、化工和自动化工业设备等工业领域。它是一种效率高、转矩重量比大、动态响应快的同步电机。为了对PMBLDC电机进行有效的速度控制,采用粒子群优化算法对PID控制器进行整定,该算法具有简单、收敛速度快等优点。与传统的Zeigler-Nichols方法(Z-N)和进化遗传算法(GA)相比,采用粒子群算法调谐的PID控制器具有更快的稳定时间、可忽略峰值超调和有效的速度控制的时间响应性能。通过考虑非振荡、振荡、积分和非最小相位等各种系统的数值例子来强调这一点。结果表明,PSO-PID的性能优于其他两种方法。因此,PSO-PID算法可以有效地控制PMBLDC电机的速度,提高效率。
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Design and Implementation of Particle Swarm Optimization (PSO) Tuned PID Controller for Speed Control of Permanent Magnet Brush Less DC (PMBLDC) Motor
This paper presents the design and implementation of Particle Swarm Optimization (PSO) tuned PID controller for speed control of Permanent Magnet Brush Less DC (PMBLDC) motor using LabVIEW. PMBLDC motor is widely used in industrial applications like aeronautics, robotics, medical, food, chemical and automated industrial equipments. It is a synchronous motor with high efficiency, high torque-to-weight ratio and faster dynamic response. For effective speed control of PMBLDC motor, PID controller is tuned using Particle Swarm Optimization (PSO) algorithm due to its simplicity and fast convergence to optimum values. When compared with traditional Zeigler-Nichols method (Z-N) and evolutionary Genetic Algorithm (GA), PID controller tuned with PSO algorithm provides an improved time response performance with faster settling time, negligible peak overshoot and effective speed control. This is emphasized by considering numerical examples of various systems like non-oscillatory, oscillatory, integrating and non-minimum phase. The results obtained indicate that PSO-PID performs better than the other two methods. Hence, it is concluded that PSO-PID algorithm is ideal to control the speed of PMBLDC motor effectively with increased efficiency.
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