基于粒子群优化的感应电机最优速度控制技术

M. Eissa, G. Virk, A. M. Abdelghany, E. S. Ghith
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引用次数: 24

摘要

工业过程受到参数变化和参数扰动的影响,这在显著时使系统不稳定。为了克服这种参数变化的问题,PI控制器以其简单、鲁棒性被广泛应用于工业装置中。然而,在调整PI参数时有一个问题。所以控制工程师在寻找自动调谐程序。近年来,提出了许多智能算法来调整PI参数。使用不同的优化算法如模拟退火、遗传算法和粒子群优化算法来调整PI参数。提出了一种基于粒子群优化的异步电动机速度控制PI参数调度方法。我们的工作结果显示了一个非常低的瞬态响应和一个无振荡的稳态响应,具有良好的稳定性。仿真结果表明了该方法的有效性,对PSO-PI控制器具有满意的响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimum Induction Motor Speed Control Technique Using Particle Swarm Optimization
Industrial processes are subjected to variation in parameters and parameter perturbations, which when significant makes the system unstable. In order to overcome this problem of parameter variation the PI controllers are widely used in industrial plants because it is simple and robust. However there is a problem in tuning PI parameters. So the control engineers are on look for automatic tuning procedures. In recent years, many intelligence algorithms are proposed to tuning the PI parameters. Tuning PI parameters using different optimal algorithms such as the simulated annealing, genetic algorithm, and particle swarm optimization algorithm. In this paper a scheduling PI tuning parameters using particle swarm optimization strategy for an induction motor speed control is proposed. The results of our work have showed a very low transient response and a non-oscillating steady state response with excellent stabilization. The simulation results presented in this paper show the effectiveness of the proposed method, with satisfied response for PSO-PI controller.
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