吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (4): 1057-1061.doi: 10.13229/j.cnki.jdxbgxb201404024

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Iterative robust filtering for uncertain systems with missing measurements

FENG Jian-xin, WANG Ting-feng, GUO Jin   

  1. State Key Laboratory of Laser Interaction with Matter, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
  • Received:2013-02-21 Online:2014-07-01 Published:2014-07-01

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Abstract: An iterative robust filtering algorithm was proposed for a class of dynamic systems with input uncertainties, model parameter uncertainties and missing measurements. A norm-bounded variable was used to describe the system input uncertainties and model parameter uncertainties. The phenomenon that the measured data is missing during the transmission obeys a stochastic binary switch sequence with a known conditional probability distribution. A least-square robust filter was obtained via min-max game theory. Then, on this basis, the desired iterative robust filter was designed via an iterative tactic. Simulation results demonstrate the effectiveness of the proposed approaches.

Key words: automatic control technology, uncertainty, missing measurements, game theory, iterative robust filtering

CLC Number: 

  • TP273
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