Results 261 to 270 of about 5,705,352 (293)
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Embedding of Nonlinear Systems in a Linear Parameter-Varying Representation
IFAC Proceedings Volumes, 2014This paper introduces a systematic approach to synthesize linear parameter-varying (LPV) representations of nonlinear (NL) systems which are originally defined by control affine state-space representations. The conversion approach results in LPV state-space representations in the observable canonical form.
Abbas, Hossam S. +4 more
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Recursive subspace identification of linear parameter-varying systems
2012 American Control Conference (ACC), 2012In this paper, a recursive algorithm for blackbox identification of linear parameter-varying (LPV) systems is proposed. The algorithm belongs to the class of subspace identification methods and is based on an existing LPV subspace identification algorithm with block-processing, which is modified and extended to the recursive estimation scenario.
Michael Buchholz, Samuel Werner
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Geometric Theory and Control of Linear Parameter Varying Systems
2007 4th International Symposium on Applied Computational Intelligence and Informatics, 2007Linear Parameter Varying (LPV) systems appear in a form of LTI state space representations where the elements of the A(rho), B(rho), C(rho) matrices depend on an unknown but at any time instant measurable vector parameter rho isin V. This paper describes a geometric view of LPV systems. Geometric concepts and tools of invariant subspaces and algorithms
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Polytopic linear parameter-varying model of epileptiform activity
Proceedings of the 2010 American Control Conference, 2010A novel abstract modeling approach for brain dynamics exhibiting epileptiform activity is proposed, and a seizure prediction algorithm based on this approach is presented. The model consists of several polytopes of parameters, each of which corresponds to a particular brain dynamics, and a seizure onset is predicted when real time-identified model ...
Tingting Lu, Ji-Woong Lee
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Stability results for linear parameter varying and switching systems
Automatica, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
BLANCHINI, Franco +2 more
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Complexity of Implementation and Synthesis in Linear Parameter-Varying Control
IFAC Proceedings Volumes, 2014In this paper an analysis of the complexity involved in the implementation and synthesis of linear parameter-varying (LPV) controllers is presented. Its purpose is to provide guidance in the selection of a synthesis approach for practical LPV control problems and reveal directions for further research with respect to complexity issues in LPV control ...
Hoffmann, Christian, Werner, Herbert
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On the discretization of LMI-synthesized linear parameter-varying controllers
Automatica, 1997The author studies discretization of control systems whose dynamics is linear. He discusses methods based on linear matrix inequalities to synthesize gain-scheduled controllers. The implementation and the computational cost of these methods are studied. Simulations for a two-link manipulator control problem are presented.
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Distributed control for distributed linear parameter varying systems
Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148), 2001Considers stability analysis and performance control for distributed systems with time and spatial varying parameters. The distributed linear parameter-varying (LPV) system depends on the parameters in linear fractional transformation form. The parameters are assumed measurable in real-time for controller use.
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The most powerful unfalsified linear parameter-varying model
AutomaticaThe most powerful unfalsified model (MPUM), i.e., the least complex exact model for the given data, is well established for linear time-invariant (LTI) systems. It has not been generalized for linear parameter-varying (LPV) systems. In order to do this, we define the notions of complexity for LPV systems with shifted-affine scheduling dependence.
Ivan Markovsky +2 more
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Ellipsoidal Set-Membership Filtering for Discrete-Time Linear Time-Varying Systems
IEEE Transactions on Automatic Control, 2023Mouquan Shen, Yi Shen, Yilian Zhang
exaly