Results 141 to 150 of about 9,176 (173)
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Failure detection for quasi LPV systems
Proceedings of the 41st IEEE Conference on Decision and Control, 2002., 2003By using the concept of parameter varying (CA)invariant subspace and parameter varying unobservability subspace, this paper investigates the problem of fault detection and isolation for quasi linear parameter varying (qLPV) systems. The so called detection filters approach, formulated as the fundamental problem of residual generation (FPRG) for linear ...
József Bokor +2 more
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A Method of LPV Model Identification for Control
IFAC Proceedings Volumes, 2008Nonlinear process identification for control is studied. In identification test, the process is only tested (excited) along its operating-trajectory that includes various working points and transition periods. In model identification, a linear parameter varying (LPV) model is used.
Zhu, Y., Xu, Zuhua
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LPV Equivalence Transformations
2010In this chapter, we continue the discussion of the LPV behavioral framework by establishing equivalence transformations between the state-space and the input-output representation domains. These equivalence transformations enable the comparison and analysis of LPV model structures and provide essential tools to formulate the identification approach of ...
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2014
This chapter first presents the main stability and instability results for general dynamical systems. These results are then further adapted to the analysis of linear parameter-varying systems in the generic, polytopic and LFT frameworks. Notably, the notions of quadratic and robust stability using quadratic Lyapunov functions are introduced.
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This chapter first presents the main stability and instability results for general dynamical systems. These results are then further adapted to the analysis of linear parameter-varying systems in the generic, polytopic and LFT frameworks. Notably, the notions of quadratic and robust stability using quadratic Lyapunov functions are introduced.
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Polytopic LPV approaches for intelligent automotive systems: State of the art and future challenges
Mechanical Systems and Signal Processing, 2021Hui Zhang, Haiping Du, Anh-Tu Nguyen
exaly
2014
This chapter is devoted to the development of control-laws for linear parameter-varying systems. The LPV framework allows for an easy design of gain-scheduled controllers, that is, controllers whose state-space structure depends on the value of the parameters thereby used as scheduling variables.
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This chapter is devoted to the development of control-laws for linear parameter-varying systems. The LPV framework allows for an easy design of gain-scheduled controllers, that is, controllers whose state-space structure depends on the value of the parameters thereby used as scheduling variables.
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2010
This chapter is devoted to the discretization of LPV systems through the discrete-time projection of their state-space representations. Both exact and approximative approaches are developed in a zero-order hold setting. Primary attention is given to the discretization of state-space representations with static coefficient dependence.
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This chapter is devoted to the discretization of LPV systems through the discrete-time projection of their state-space representations. Both exact and approximative approaches are developed in a zero-order hold setting. Primary attention is given to the discretization of state-space representations with static coefficient dependence.
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2014
The goal of this chapter is to introduce the main ways for representing linear parameter-varying systems and emphasize their ability to represent a wide class of dynamical systems. A classification of the types of parameters regarding their mathematical properties and their physical meaning is also given.
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The goal of this chapter is to introduce the main ways for representing linear parameter-varying systems and emphasize their ability to represent a wide class of dynamical systems. A classification of the types of parameters regarding their mathematical properties and their physical meaning is also given.
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LPV Systems and Representations
2010In this chapter, a behavioral framework of LPV systems is introduced as an extension of the LTI behavioral approach. This is done with the intention to give a unified view on LPV system theory, that enables to approach LPV system identification in a well-founded system theoretic sense.
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2012
The framework of Linear Parameter Varying (LPV) systems concerns linear dynamical systems whose state-space representations depend on exogenous nonstationary parameters. Since its introduction by Shamma and Athans in 1988 to model gain-scheduling, the LPV paradigm has become a standard formalism in systems and controls, with many papers devoted to ...
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The framework of Linear Parameter Varying (LPV) systems concerns linear dynamical systems whose state-space representations depend on exogenous nonstationary parameters. Since its introduction by Shamma and Athans in 1988 to model gain-scheduling, the LPV paradigm has become a standard formalism in systems and controls, with many papers devoted to ...
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