Receding-horizon estimation for switching discrete-time linear systems

Receding-horizon state estimation is addressed for a class of discrete-time systems that may switch among different modes taken from a finite set. The system and measurement equations for each mode are assumed to be linear and perfectly known, but the current mode of the system is unknown, the state...

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Bibliographic Details
Published in:IEEE transactions on automatic control 2005-11, Vol.50 (11), p.1736-1748
Main Authors: Alessandri, A., Baglietto, M., Battistelli, G.
Format: Article
Language:English
Subjects:
Applied sciences
Computer science
control theory
systems
Control theory. Systems
Convergence
Cost function
Current measurement
Disturbances
Equations
Estimators
Exact sciences and technology
Linear systems
Mathematical analysis
Mathematical models
Modelling and identification
Noise measurement
Observability
receding horizon
State estimation
State vectors
Studies
Switches
switching systems
Vectors
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Summary:Receding-horizon state estimation is addressed for a class of discrete-time systems that may switch among different modes taken from a finite set. The system and measurement equations for each mode are assumed to be linear and perfectly known, but the current mode of the system is unknown, the state variables are not perfectly measurable and are affected by disturbances. The system mode is regarded as an unknown discrete state to be estimated together with the continuous state vector. Observability conditions are found to distinguish the system mode in the presence of bounded system and measurement noises. These results allow one to construct an estimator that relies on the combination of the identification of the discrete state with the estimation of the state variables by minimizing a receding-horizon quadratic cost function. The convergence properties of such an estimator are studied, and simulation results are reported to show the effectiveness of the proposed approach.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2005.858684