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Robust fault and state estimation for linear discrete-time systems with unknown disturbances using PI Three-Stage Kalman Filter

机译:使用PI三级卡尔曼滤波器具有未知干扰线性离散系统的强大故障和状态估计

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摘要

The problem of simultaneously estimating the state and the fault of linear time varying stochastic systems in the presence of unknown input with uncertain noise covariances is presented. The approach suggested rests on the use of the Proportional Integral Three-Stage Kalman Filter (PI-ThSKF). This technique is qualified to be robust against the noise covariance matrices uncertainty. The proposed filter is tested by an illustrative example.
机译:呈现了同时估计线性时间变化随机系统在存在未知噪声Coveramce的未知输入中的状态和断层的问题。该方法建议基于使用比例整体三级卡尔曼滤波器(PI-THSKF)。该技术有资格对噪声协方差矩阵不确定性稳健。通过说明性示例测试所提出的滤波器。

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