Stochastic boundedness filter design for Markovian jump linear systems with guaranteed H∞ filtering performance

Stochastic boundedness filter design for Markovian jump linear systems with guaranteed H∞ filtering performance
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马尔可夫跳跃线性系统的随机有界滤波器设计,保证 H 滤波性能

DOI:
10.1177/0142331216645177
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发表时间:
2017-11
影响因子:
1.8
通讯作者:
Sheng Liu
Sheng Liu
中科院分区:
计算机科学4区
文献类型:
--
作者:
Yuchao Wang;Huixuan Fu;Sheng Liu

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研究一类连续时间马尔可夫跳变线性系统的滤波问题,该系统假定马尔可夫跳变在短时间间隔内频繁发生。对于这类马尔可夫跳跃系统,估计误差的有界性值得我们研究。通过引入有限时间区间的随机有界性概念,构造了一个保证估计误差有界于规定边界的观测器,并将结果推广到具有范数有界扰动的H∞滤波问题。通过构造一种优化算法,推导出具有估计误差边界和H∞性能指标优化凸组合的最优H∞随机有界滤波器。当涉及参数优化时,我们提出了一种设计算法。数值设计实例说明了本文结果的有效性。
This paper concerns the filtering problem for a class of continuous-time Markovian jump linear systems, where the Markovian jump is supposed to frequently occur in some short time intervals. For this class of Markovian jump system, the boundedness of estimation error deserves our investigation. By introducing the concepts of stochastic boundedness with respect to a finite-time interval, an observer ensuring the estimation error bounded in a prescribed boundary is constructed and the result is extended to the H ∞ filtering problem with norm bounded disturbances. By formulating an optimization algorithm, we derive the optimal H ∞ stochastic boundedness filter with an an optimized convex combination of estimation error boundary and H ∞ performance index. We propose a design algorithm for when parameter optimization is involved. Numerical design examples are given to illustrate the effectiveness of our results.
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