Discretization of Linear Fractional Representations of LPV systems
Roland Tóth,Marco Lovera,Peter S. C. Heuberger,P.M.J. Van den Hof +3 more
- pp 7424-7429
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.read more
Citations
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Proceedings ArticleDOI
Inversion based FDI for sampled LPV systems
TL;DR: In this article, a method for the construction of the inverse, relying on the concept of parameter varying invariant subspaces and related concepts of classical geometrical system theory, is presented.
Proceedings ArticleDOI
Direct identification of continuous-time LPV models
TL;DR: To provide consistent model parameter estimates in this setting, a refined instrumental variable approach is proposed and the statistical properties of this approach are demonstrated through a Monte Carlo simulation example.
Proceedings ArticleDOI
Stochastic model predictive control for LPV systems
TL;DR: The prediction dynamics for LPV systems are reposed in an augmented form, which facilitates the feasibility of probabilistic constraints and closed-loop stability in the presence of stochastic uncertainties.
Proceedings ArticleDOI
Discrete LPV Modeling of Diabetes Mellitus for Control Purposes
TL;DR: An analysis of the available discretization options in order to develop discrete models with a special focus on the Linear Parameter Varying (LPV) systems is performed.
Proceedings ArticleDOI
LPV Model Of Wind Turbines From GH Bladed's Linear Models.
TL;DR: This paper shows a strategy to carry out a wind turbine LPV and MIMO (Multivariable Input and Multivariable Output) model from a family of LTI (Linear Time Invariant) models.
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