An innovation representation for nonlinear systems with application to parameter and state estimation

DOI10.1016/0005-1098(94)90058-2zbMath0834.93051OpenAlexW2061111798MaRDI QIDQ1344376

V. Pereyra

Publication date: 12 March 1995

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2027.42/31179

zbMATH Keywords

parameter estimationnonlinear stochastic systemrecursive prediction error algorithm

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12)

Related Items (1)

Sliding-window neural state estimation in a power plant heater line

Cites Work

• On covariance function tests used in system identification
• A computationally efficient technique for state estimation of nonlinear systems
• Stochastic processes and filtering theory
• State-space adaptive control through a modified bootstrap algorithm for parameter and state estimation
• Robust pole assignment in linear state feedback
• A modified state-space approach to multivariable self-tuning control with pole assignment
• Recursive Prediction Error Methods for Adaptive Estimation
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: An innovation representation for nonlinear systems with application to parameter and state estimation