Applicability of least-squares to the parameter estimation of large-scale no-memory linear composite systems

DOI10.1080/00207728908910324zbMath0686.93087OpenAlexW2009875274MaRDI QIDQ4205375

Zygmunt Hasiewicz

Publication date: 1989

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207728908910324

zbMATH Keywords

least-squares algorithmcomposite system parameterslarge-scale interconnected static linear system

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Estimation and detection in stochastic control theory (93E10) Large-scale systems (93A15)

Related Items (3)

Identification of non-linear characteristics of a class of block-oriented non-linear systems via Daubechies wavelet-based models ⋮ Nonparametric instrumental variables for identification of block-oriented systems ⋮ Instrumental variables for nonlinearity recovering in block-oriented systems driven by correlated signals

Cites Work

• Persistency of excitation, sufficient richness and parameter convergence in discrete time adaptive control
• Persistence of excitation in extended least squares
• Augmented decentralized control with local feedback for steady-state systems
• An integrated system optimization and parameter estimation technique for hierarchical control of steady-state systems
• Identifiability of large-scale interconnected linear zero-memory systems
• Improved least squares identification
• Optimal structures for steady-state adaptive optimizing control of large-scale industrial processes
• Linear Statistical Inference and its Applications

This page was built for publication: Applicability of least-squares to the parameter estimation of large-scale no-memory linear composite systems