直流电机PID控制的粒子群算法整定

Eka Suci Rahayu, A. Ma’arif, Abdullah Çakan
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引用次数: 18

摘要

直流电动机的使用由于其自身的优点而变得普遍,并已成为帮助人类活动的重要必需品。电机控制一般采用PID控制设计。PID中经常讨论的主要问题是参数整定,即确定Kp、Ki和Kd参数的值,以获得最优的系统性能。在本研究中,将使用一种方法对直流电机的PID参数进行整定,即粒子群优化(PSO)方法。与其他方法相比,粒子群方法的参数优化结果稳定。在MATLAB Simulink上采用PSO方法对PID控制器参数进行整定,得到Kp = 8.9099, K = 2.1469, Kd = 0.31952,上升时间为0.0740,沉降时间为0.1361,超调量为0的最优结果。然后在Arduino IDE软件中输入PID值进行硬件测试,得到稳定的电机转速响应,Kp = 1.4551, Ki= 1.3079, Kd = 0.80271,上升时间值为4.3296,稳定时间为7.3333,超调值为1。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Particle Swarm Optimization (PSO) Tuning of PID Control on DC Motor
The use of DC motors is now common because of its advantages and has become an important necessity in helping human activities. Generally, motor control is designed with PID control. The main problem that is often discussed in PID is parameter tuning, namely determining the value of the Kp, Ki, and Kd parameters in order to obtain optimal system performance. In this study, one method for tuning PID parameters on a DC motor will be used, namely the Particle Swarm Optimization (PSO) method. Parameter optimization using the PSO method has stable results compared to other methods. The results of tuning the PID controller parameters using the PSO method on the MATLAB Simulink obtained optimal results where the value of Kp = 8.9099, K = 2.1469, and Kd = 0.31952 with the value of rise time of 0.0740, settling time of 0.1361 and overshoot of 0. Then the results of hardware testing by entering the PID value in the Arduino IDE software produce a stable motor speed response where Kp = 1.4551, Ki= 1.3079, and Kd = 0.80271 with a rise time value of 4.3296, settling time of 7.3333 and overshoot of 1.
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