Kalman Filter as an Alternative to Extended State Observer in ADRC Control Algorithm

Jacek Michalski, Mikołaj Mrotek, Piotr Kozierski
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Abstract

The article presents a modified Active Disturbance Rejection Control (ADRC) algorithm that uses the Kalman Filter (KF) for the estimation of extended state vector. The Kalman filter replaced the Extended State Observer (ESO) used in its basic form. The purpose of this modification was to improve the system robustness under conditions of stochastic measurement disturbances. The method of the control system synthesis and the Kalman filter gains selection, ensuring control efficiency, as well as their impact on the system operation, were presented. The experiments were carried out on a laboratory setup – the Ball Balancing Table (BBT). Control quality was assessed based on time plots of signals and integral performance indices for various algorithm gains configurations and different noise levels. As a result of the conducted research, the advantage of using the Kalman filter over the ESO in terms of sensitivity to measurement noises was demonstrated. Implementation of the Kalman filter as the ESO determined a positive impact on control quality and the ability to reject internal disturbance also in a deterministic system.
卡尔曼滤波器替代 ADRC 控制算法中的扩展状态观测器
文章介绍了一种改进的主动干扰抑制控制(ADRC)算法,该算法使用卡尔曼滤波器(KF)来估计扩展状态向量。卡尔曼滤波器取代了基本形式中使用的扩展状态观测器(ESO)。这一修改的目的是提高系统在随机测量干扰条件下的鲁棒性。介绍了控制系统合成和卡尔曼滤波器增益选择的方法,以确保控制效率,以及它们对系统运行的影响。实验在实验室装置--球形平衡台(BBT)上进行。根据各种算法增益配置和不同噪声水平下的信号时间图和积分性能指标,对控制质量进行了评估。研究结果表明,在对测量噪声的敏感性方面,使用卡尔曼滤波器比使用 ESO 更有优势。采用卡尔曼滤波器作为 ESO 对控制质量和确定性系统的内部干扰抑制能力具有积极影响。
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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