Title :
Model-set adaptation in variable-structure MM estimation by hypothesis testing
Author_Institution :
Dept. of Electr. Eng., New Orleans Univ., LA, USA
Abstract :
The key component in variable-structure multiple-model (MM) estimation is model-set adaptation (MSA). This paper formulates MSA as hypothesis testing problems and provides effective solutions, which have some desirable optimality properties. The hypotheses tested are in general composite, N-ary, multivariate, and worst of all, not necessarily disjoint. The results form a theoretical foundation and guideline for developing good and practical MSA algorithms
Keywords :
set theory; state estimation; statistical analysis; variable structure systems; hypothesis testing; model-set adaptation; recursive adaptive model set; set theory; state estimation; statistical analysis; variable-structure estimation; variable-structure multiple-model; Adaptation model; Costs; Delay; Filters; Power system modeling; State estimation; Testing; Uncertainty;
Conference_Titel :
American Control Conference, 1998. Proceedings of the 1998
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-4530-4
DOI :
10.1109/ACC.1998.703072
