基于扩展卡尔曼滤波估计的磁悬浮系统采样数据滑模控制

Neelma Naz, M. Malik, Asim Zaheer, M. Salman
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引用次数: 1

摘要

提出了一种基于采样数据输出反馈结构的磁悬浮系统滑模控制方法。同时考虑了监管和跟踪问题。由于在实时系统上实施控制方案时并非所有状态都可用,或者由于工厂输出端的传感器噪声而获得有噪声的输出数据。为此,采用基于扩展卡尔曼滤波的估计器来估计对象的无噪声和未知状态。在参数摄动/不确定性和外部干扰下,对控制系统进行了鲁棒性测试。计算机仿真结果表明了控制系统的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sampled Data Sliding Mode Control of Magnetic Levitation System Using Extended Kalman Filter Estimator
In this paper, A Sliding Mode Control of Magnetic Levitation system for sampled data output feedback configuration is presented. Both regulation and tracking problems are considered. As all states are not available while control scheme is implemented on real time systems or a noisy output data is obtained because of sensor noise at the plant's output. For this purpose Extended Kalman Filter based estimator is employed to estimate the noise free and unknown states of plant. The control system is also tested under parametric perturbations/uncertainties and external disturbance to prove its robustness. Computer simulations show robust performance of control system.
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