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An improved particle swarm optimization algorithm for parameter optimization of proportional-integral-derivative controller

机译:比例整体衍生控制器参数优化改进的粒子群优化算法

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摘要

The performance of automatic control systems hinges on the parameters of proportional-integral-derivative (PID) controller. Therefore, this paper attempts to determine the most suitable parameter values of PID controller. For this purpose, the particle swarm optimization (PSO) was improved after introducing the flying time T and adaptive weight ω, and the improved PSO (IPSO) was compared against the basic PSO and the PSO modified with both inertial weight and constriction factor (PSO-ω, x). After that, the IPSO was applied to optimize the parameters of the PID controller. With a second-order inertia model as the control object, the parameters of PID controller optimized by the IPSO were contrasted with those optimized by the traditional Ziegler-Nichols optimization method. The results show that the IPSO is faster and more accurate than the traditional approach. The research findings provide new insights into the optimization of the PID controller and the application of the PSO.
机译:自动控制系统铰接对比例积分 - 衍生(PID)控制器参数的性能。因此,本文试图确定PID控制器最合适的参数值。为此目的,在引入飞行时间T和自适应权重ω后,改善了粒子群优化(PSO),并将改进的PSO(IPSO)与惯性重量和收缩因子(PSO)进行了改进的基本PSO和PSO进行了比较(PSO -ω,x)。之后,应用IPSO以优化PID控制器的参数。通过作为控制对象的二阶惯性模型,由IPSO优化的PID控制器参数与由传统的Ziegler-Nichols优化方法优化的人鲜明对比。结果表明,IPSO比传统方法更快,更准确。研究结果为PID控制器的优化和PSO的应用提供了新的见解。

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