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Optimal discrete-time H-infinity/gamma(0) filtering and control under unknown covariances

机译:未知协方差下的最佳离散时间H-infinity / gamma(0)滤波和控制

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摘要

New stochastic gamma(0) and mixed H-infinity/gamma(0) filtering and control problems for discrete-time systems under completely unknown covariances are introduced and solved. The performance measure gamma(0) is the worst-case steady-state averaged variance of the error signal in response to the stationary Gaussian white zero-mean disturbance with unknown covariance and identity variance. The performance measure H-infinity/gamma(0) is the worst-case power norm of the error signal in response to two input disturbances in different channels, one of which is the deterministic signal with a bounded energy and the other is the stationary Gaussian white zero-mean signal with a bounded variance provided the weighting sum of disturbance powers equals one. In this framework, it is possible to consider at the same time both deterministic and stochastic disturbances highlighting their mutual effects. Our main results provide the complete characterisations of the above performance measures in terms of linear matrix inequalities and therefore both the gamma(0) and H-infinity/gamma(0) optimal filters and controllers can be computed by convex programming. H-infinity/gamma(0) optimal solution is shown to be actually a trade-off between optimal solutions to the H-infinity and gamma(0) problems for the corresponding channels.
机译:引入并解决了完全未知协方差下离散时间系统的新随机gamma(0)和混合H-infinity / gamma(0)滤波和控制问题。性能度量gamma(0)是响应于具有未知协方差和恒等方差的平稳高斯白色零均值扰动的误差信号的最坏情况稳态平均方差。性能量度H-infinity / gamma(0)是响应不同通道中的两个输入干扰时误差信号的最坏情况功率范数,其中一个是具有有限能量的确定性信号,另一个是平稳的高斯信号如果干扰功率的加权和等于1,则具有有限方差的白色零均值信号。在此框架中,可以同时考虑确定性干扰和随机性干扰,以突出其相互影响。我们的主要结果提供了上述性能度量的线性矩阵不等式的完整表征,因此,可以通过凸编程来计算gamma(0)和H-infinity / gamma(0)最优滤波器和控制器。 H-infinity / gamma(0)最佳解决方案实际上是针对相应通道的H-infinity和gamma(0)问题的最佳解决方案之间的折衷方案。

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