On the State-Space Realization of LPV Input-Output Models: Practical Approaches

A common problem in the context of linear parameter-varying (LPV) systems is how input-output (IO) models can be efficiently realized in terms of state-space (SS) representations. The problem originates from the fact that in the LPV literature discrete-time identification and modeling of LPV systems...

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Bibliographic Details
Published in:	IEEE transactions on control systems technology Vol. 20; no. 1; pp. 139 - 153
Main Authors:	Toth, R., Abbas, H. S., Werner, H.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.01.2012 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Applied sciences Approximation Approximation error Atmospheric modeling Computer science; control theory; systems Control system analysis Control theory. Systems Dynamic dependence Dynamic scheduling Dynamical systems Dynamics Equivalence Exact sciences and technology input-output (IO) representation linear parameter-varying (LPV) systems Markov processes Mathematical analysis model reduction Modelling and identification Operational research and scientific management Operational research. Management science Polynomials realization Representations Scheduling Scheduling, sequencing state-space (SS) representation Studies Trajectory Transformations System realization Kalman filter Dynamic dependence model reduction Linear parameter varying system State space Scheduling State space method Linear control state-space (SS) representation realization Time varying system Linear time invariant system Instantaneous value input-output (IO) representation Discrete time Approximation error Delay time Reduced order systems System identification linear parameter-varying (LPV) systems State estimation Input output model
ISSN:	1063-6536, 1558-0865
Online Access:	Get full text
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