An observer based adaptive PID controller

L. Yao, Hong-Kang Wen
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引用次数: 1

Abstract

An Adaptive Fuzzy PID Controller with Genetic Algorithm (GA) to tune its parameters is proposed in this paper. The task of the controller is to track the trajectory of a nonlinear system as best as it could. The Lyapunov's direct method is used as a tool for nonlinear system analysis and design. In which, the Lyapunov's linearization method is proven here to be useful for linear control. The paper relies on linearization method and the direct method to formulate its stability theory. The controller has two states, a learning state and a controlling state where GA performs on-line tuning of the controller's parameters. The GA method has the effect of tuning PID parameters to meet operation time constraint and system performance. In the controlling state, there are a supervisory controller designed to ensure system stability and a compensator appended to compensate for modeling error and disturbance. Overall performance of the controller is not compromised by the fact that it has only three parameters to work with.
一种基于观测器的自适应PID控制器
提出了一种采用遗传算法进行参数整定的自适应模糊PID控制器。控制器的任务是尽可能地跟踪非线性系统的轨迹。李雅普诺夫直接法被用作非线性系统分析和设计的工具。其中,李雅普诺夫线性化方法在线性控制中是有用的。本文采用线性化法和直接法来建立其稳定性理论。控制器有两种状态,一种是学习状态,另一种是控制状态,其中遗传算法对控制器的参数进行在线调整。遗传算法具有自整定PID参数以满足运行时间约束和系统性能要求的效果。在控制状态下,设计了一个监控控制器来保证系统的稳定性,并附加了一个补偿器来补偿建模误差和干扰。控制器的整体性能不会因为它只有三个参数而受到影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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