Multiresolution Fusion Estimation of Dynamic Multiscale System Subject to Nonlinear Measurement Equation

• Published in: Advances in Intelligent Computing pp. 405 - 413
• Main Authors: Cui, Peiling, Pan, Quan, Wang, Guizeng, Cui, Jianfeng
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Extend Kalman Filter; IEEE Transaction; Measurement Noise; Radial Distance; True State; Monte Carlo method; Wavelet transformation; Multiscale method; Dynamical system; Control theory; Haar function; Artificial intelligence; Modeling; Multiresolution analysis
• ISBN: 3540282270; 9783540282273; 3540282262; 9783540282266
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11538356_42

Fusion of the states of a nonlinear dynamic multiscale system (DMS) on the basis of available noisy measurements is one of the well-known key problems in modern control theory. To the best of our knowledge, all of the previous work focused attention on linear DMS. However, nonlinear DMS has never been investigated. In this paper, modeling and fusion estimation of dynamic multiscale system subject to nonlinear measurement equation is proposed. Haar wavelet is used to link the scales. Monte Carlo simulation results demonstrate that the proposed algorithm is effective and powerful in this kind of nonlinear dynamic multiscale system estimation problem.