Weighted least squares based recursive parametric identification for the submodels of a PWARX system

DOI10.1016/j.automatica.2012.03.015zbMath1244.93168OpenAlexW2054782569MaRDI QIDQ445160

Tong Zhou, Wen-Xiao Zhao

Publication date: 24 August 2012

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2012.03.015

zbMATH Keywords

recursive identificationkernel functionhybrid systemstrong consistencyweighted least squares

Mathematics Subject Classification ID

Identification in stochastic control theory (93E12) Control/observation systems governed by functional relations other than differential equations (such as hybrid and switching systems) (93C30)

Related Items (3)

Pseudo-predictor feedback stabilization of linear systems with time-varying input delays ⋮ Variational Bayesian approach for ARX systems with missing observations and varying time-delays ⋮ An Iterative Algebraic Geometric Approach for Identification of Switched ARX Models with Noise

Cites Work

• Unnamed Item
• Adaptive control of Wiener type nonlinear systems
• A case study of Grey Box identification
• Identification of piecewise affine systems via mixed-integer programming.
• A clustering technique for the identification of piecewise affine systems
• Support-vector networks
• Nonlinear black-box modeling in system identification: A unified overview
• Identification of hybrid systems. A tutorial
• Identification of piecewise affine systems based on statistical clustering technique
• Recursive prediction error identification and scaling of non-linear state space models using a restricted Black box parameterization
• Analysis of recursive stochastic algorithms
• Recursive Identification for Nonlinear ARX Systems Based on Stochastic Approximation Algorithm
• Non-Parametric Nonlinear System Identification: An Asymptotic Minimum Mean Squared Error Estimator
• A Bayesian approach to identification of hybrid systems
• A bounded-error approach to piecewise affine system identification
• Identification of IIR Nonlinear Systems Without Prior Structural Information

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