State estimation for Markovian Jump Linear Systems with bounded disturbances
State estimation for Markovian Jump Linear Systems with bounded disturbances
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DOI：
10.1016/j.automatica.2013.08.030
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发表时间：
2013-11
期刊：
影响因子：
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通讯作者：
Hao Wu;Wen Wang;H. Ye;Zidong Wang
中科院分区：
文献类型：
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作者：
Hao Wu;Wen Wang;H. Ye;Zidong Wang
本文研究了一类马尔可夫跳跃线性系统(MJLSS)在有界多面体扰动下的状态估计问题。首先提出了一种集合成员估计算法来寻找所有可能状态的最小一致集合，该集合由多个多面体的并集来表示。然后通过引入勒贝格测度估计系统跳跃模式的后验概率，并在此基础上给出最优点估计。此外，定义了多面体的相似关系，给出了计算多面体Minkowski和的近似方法，从而降低了整体估计算法的计算复杂度。
In this paper, we investigate the state estimation problem for a class of Markovian Jump Linear Systems (MJLSs) in the presence of bounded polyhedral disturbances. A set-membership estimation algorithm is first proposed to find the smallest consistent set of all possible states, which is shown to be expressed by a union of multiple polytopes. The posterior probabilities of the system jumping modes are then estimated by introducing the Lebesgue measure, based on which the optimal point estimate is further provided. Moreover, asimilarityrelationship for polytopes is defined and an approximate method is presented to calculate the Minkowski sum of polytopes, which can help reduce the computational complexity of the overall estimation algorithm.