Title :
Multiple-model estimation with variable structure: model-group switching algorithm
Author :
Li, X. Rong ; Zhang, Youmin ; Zhi, Xiaorong
Author_Institution :
New Orleans Univ., LA, USA
Abstract :
A general multiple-model estimator with variable structure (VSMM), called model-group switching algorithm, is presented. It assumes that the total set of models can be covered by a number of model groups, each representing a cluster of closely related system behavior patterns or structures, and a particular group is running at any given time determined by a hard decision. This algorithm is the first VSMM estimator that is generally applicable to a large class of problem with hybrid (continuous and discrete) uncertainties and easily implementable. The algorithm is promising in the sense of being substantially more cost-effective than the interacting multiple-model estimator
Keywords :
linear systems; probability; state estimation; stochastic systems; variable structure systems; linear systems; model-group switching algorithm; multiple-model estimation; probability; state estimation; stochastic systems; variable structure; Algorithm design and analysis; Clustering algorithms; History; Noise measurement; State estimation; Stochastic systems; Target tracking; Time measurement; Uncertainty; Vectors;
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4187-2
DOI :
10.1109/CDC.1997.652320