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Discretization of Linear Fractional Representations of LPV systems

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TLDR
The proposed and existing methods are compared and analyzed in terms of approximation error, considering ideal zero-order hold actuation and sampling, and criteria to choose appropriate sampling times with respect to the investigated methods are presented.
Abstract
Commonly, controllers for Linear Parameter- Varying (LPV) systems are designed in continuous-time using a Linear Fractional Representation (LFR) of the plant. However, the resulting controllers are implemented on digital hardware. Furthermore, discrete-time LPV synthesis approaches require a discrete-time model of the plant which is often derived from continuous-time first-principle models. Existing discretization approaches for LFRs suffer from disadvantages like alternation of dynamics, complexity, etc. To overcome the disadvantages, novel discretization methods are derived. These approaches are compared to existing techniques and analyzed in terms of approximation error, considering ideal zero-order hold actuation and sampling.

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Citations
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Journal ArticleDOI

I and i

Kevin Barraclough
- 08 Dec 2001 - 
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Journal ArticleDOI

Discretisation of linear parameter-varying state-space representations

TL;DR: In this article, a survey of state-space discretisation of linear parameter-varying (LPV) systems with static and dynamic dependence on the scheduling signal is presented.
Journal ArticleDOI

On the Discretization of Linear Fractional Representations of LPV Systems

TL;DR: The proposed and existing methods are compared and analyzed in terms of approximation error, considering ideal zero-order hold actuation and sampling, and criteria to choose appropriate sampling times with respect to the investigated methods are presented.
Journal ArticleDOI

Direct identification of continuous-time linear parameter-varying input/output models

TL;DR: In this paper, the authors proposed a direct identification of CT-LPV systems in an input-output setting, focusing on the case when the noise part of the data generating system is an additive discrete-time (DT) coloured noise process.
Posted Content

Affine LPV systems: realization theory, input-output equations and relationship with linear switched systems

TL;DR: A Kalman-style realization theory for discrete-time affine LPV systems is formulated and it is shown that an input-output map has a realization by an affineLPV system if and only if it satisfies certain types of input- output equations.
References
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Book ChapterDOI

Computer Controlled Systems

TL;DR: The degree of success of a computer control application depends mainly on the effectiveness of the algorithm, which is generally designed from plant specifications and desired performance characteristics.
BookDOI

Robust and Optimal Control

Mi-Ching Tsai, +1 more
Book

Modeling and Identification of Linear Parameter-Varying Systems

Roland Tóth
TL;DR: This book aims to bridge the gap between Linear Parameter-Varying (LPV) modeling and control by investigating fundamental questions of modeling and identification by proposing a unified LPV system theory, based on a behavioral approach, giving a solid basis for an identification theory.
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