Bayesian methods for time‐varying state and parameter estimation in induction machines

DOI10.1002/acs.2511zbMath1330.93220OpenAlexW1917665576MaRDI QIDQ5743805

Mohamed Nounou, Majdi Mansouri, Moustafa M. Mohamed-Seghir, Haitham A. abu-Rub, Hazem N. Nounou

Publication date: 8 February 2016

Published in: International Journal of Adaptive Control and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/acs.2511

zbMATH Keywords

power systemsparticle filteringtime varyingstate/parameter estimation

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10) Application models in control theory (93C95) Discrete-time control/observation systems (93C55) Estimation and detection in stochastic control theory (93E10)

Related Items (2)

Parameter estimation for a class of time‐varying systems with the invariant matrix ⋮ Bayesian methods for time‐varying state and parameter estimation in induction machines

Cites Work

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• Sequential Monte Carlo Methods for Dynamic Systems
• Some Relations Between Extended and Unscented Kalman Filters
• A Differential-Algebraic Approach to Speed Estimation in an Induction Motor
• Gaussian particle filtering
• Bayesian methods for time‐varying state and parameter estimation in induction machines

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