首页> 外文会议>Decision and Control, 2000. Proceedings of the 39th IEEE Conference on >Robust Kalman filter design for hybrid systems with norm-bounded unknown nonlinearities
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Robust Kalman filter design for hybrid systems with norm-bounded unknown nonlinearities

机译:具有未知范数界的混合系统的鲁棒卡尔曼滤波器设计

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Considers the filtering problem for a class of linear hybrid systems with nonlinear uncertainties and Markovian jump parameters. The unknown nonlinearities in the system are time-varying and norm-bounded. First, we show the equivalence of the norm bounded linear and nonlinear uncertainty sets. Then, instead of the original hybrid linear system with nonlinear uncertainties, we consider the same system with linear uncertainties. By using a Riccati equation approach for this new system, a robust filter is designed using two sets of coupled Riccati-like equations such that the estimation error is guaranteed to have an upper bound.
机译:考虑一类具有非线性不确定性和马尔可夫跳跃参数的线性混合系统的滤波问题。系统中未知的非线性是随时间变化且受范数约束的。首先,我们证明了范数有界线性和非线性不确定性集的等价性。然后,代替具有非线性不确定性的原始混合线性系统,我们考虑具有线性不确定性的相同系统。通过针对该新系统使用Riccati方程方法,使用两组耦合的Riccati式方程设计了鲁棒滤波器,从而确保了估计误差的上限。

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