RLS parameter convergence with overparameterized models

DOI10.1016/0167-6911(89)90006-6zbMath0669.93079OpenAlexW2036849516MaRDI QIDQ1119237

Weiping Lu, D. Grant Fisher

Publication date: 1989

Published in: Systems \& Control Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-6911(89)90006-6

zbMATH Keywords

algorithmtime-invariantoverparameterized modelsLyapunov type functionrecursive least-squares

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Estimation and detection in stochastic control theory (93E10) Linear systems in control theory (93C05) Identification in stochastic control theory (93E12) Synthesis problems (93B50)

Related Items (1)

Modified recursive least-squares algorithm for parameter identification

Cites Work

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• Exponential convergence of adaptive identification and control algorithms
• Persistency of excitation for nonminimal models of systems having purely deterministic disturbances
• Persistency of excitation in the presence of possibly unbounded signals
• On adaptive estimation and pole assignment of overparametrized systems
• Persistence of excitation in extended least squares
• On the concept of excitation in least squares identification and adaptive control^†
• Extended least squares and their applications to adaptive control and prediction in linear systems
• Remarks on persistency of excitation for nonminimal models of systems having purely deterministic disturbances
• Persistency of excitation results for structured nonminimal models
• Recursive identification of overparametrized systems
• The convergence of AML
• Analysis of recursive stochastic algorithms

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