Identification of bilinear systems with white noise inputs: An iterative deterministic-stochastic subspace approach

IEEE Transactions on Control Systems Technology

Volumn 17, Issue 5, 2009, Pages 1145-1153

  Lopes dos Santos, Paulo ^a   Ramos, José A ^b   Martins de Carvalho, Jorge L ^a  

^a UNIVERSITY OF PORTO   (Portugal)

^b NOVA SOUTHEASTERN UNIVERSITY   (United States)

Author keywords

Bilinear Kalman filtering; Bilinear systems; Hankel matrices; State space methods; Subspace identification

Indexed keywords

BILINEAR KALMAN FILTERING; BILINEAR MODELS; BILINEAR SYSTEM; BILINEAR SYSTEMS; CONSISTENCY CONDITIONS; CURSE OF DIMENSIONALITY; DATA MATRICES; HANKEL DATA; HANKEL MATRICES; LINEAR KALMAN FILTERS; LINEAR SUBSPACE; MODEL PARAMETERS; MULTI-INPUT MULTI-OUTPUT; NUMBER OF BLOCKS; PARAMETER ESTIMATE; SECOND ORDERS; STATE SPACE; STATE SPACE SYSTEMS; STOCHASTIC SUBSPACE; SUBSPACE IDENTIFICATION; UNIFORMLY CONVERGENT; WHITE NOISE INPUT; WHITE NOISE PROCESS;

CONTROL THEORY; IDENTIFICATION (CONTROL SYSTEMS); KALMAN FILTERS; LINEAR SYSTEMS; MATRIX ALGEBRA; STATE SPACE METHODS; WHITE NOISE;

ALGORITHMS;

EID: 70049088261     PISSN: 10636536     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCST.2008.2002041     Document Type: Article

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