Polynomially parameter dependent exponential stabilization of sampled-data LPV systems

H.I. Jung, S.Y. Han, Satnesh Singh and S.M. Lee

Applied Mathematics and Computation, 2021, vol. 411, issue C

Abstract: This paper proposes a polynomially sampled parameter dependent controller design for sampled-data linear parameter varying (LPV) systems. The goal of this study is to design a controller which exponentially stabilizes the system with a larger maximum sampling interval. To achieve this, we utilize the information of the parameters in the controller part. The proposed controller is dependent on the polynomials with respect to the sampled parameters, which is more effective to stabilize the system with a larger maximum sampling interval. To design the controller, an exponential stabilization condition is derived from a new Polynomially Parameter Dependent Quadratic Lyapunov Function with Looped-Functionals (PPDQLLF) which is dependent on the parameters of a plant. The derived condition is represented in terms of the linear matrix inequality (LMI) and it is formulated as sum of squares (SOS) conditions to obtain feasible solutions. The effectiveness of the proposed method is shown by the simulation results of numerical examples.

Keywords: LPV Systems; Exponential stabilization; Sampled parameter dependent controller; Sum of squares; Looped-functionals (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:411:y:2021:i:c:s0096300321005622

DOI: 10.1016/j.amc.2021.126473

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