Sampled-data LPV Control: a Looped Functional Approach**J. V. Flores and J. M. Gomes da Silva, Jr. are supported by the Brazilian National Council for Research (CNPq) under Grant Nos. 443979/2014-6, 480638/2012-8 and 306210/2009-6. V.M. Moraes and A.H.K. Palmeira are supported by CAPES scholarships, Brazil.

Silva, J.M. Gomes da; Moraes, Vitor M.; Flores, Jeferson Vieira; Palmeira, Alessandra Helena Kimura

doi:10.1016/j.ifacol.2015.11.107

IFAC-PapersOnLine

2015

DOI: 10.1016/j.ifacol.2015.11.107

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Sampled-data LPV Control: a Looped Functional Approach**J. V. Flores and J. M. Gomes da Silva, Jr. are supported by the Brazilian National Council for Research (CNPq) under Grant Nos. 443979/2014-6, 480638/2012-8 and 306210/2009-6. V.M. Moraes and A.H.K. Palmeira are supported by CAPES scholarships, Brazil.

J.M. Gomes da Silva

Vitor M. Moraes

Jeferson Vieira Flores

et al.

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On stability and H_∞ control synthesis of sampled‐data systems: A multiple convex function approximation approach

Ji,

Jiang,

Sun

et al. 2024

Intl J Robust & Nonlinear

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This article deals with the stability and control synthesis for a class of linear sampled‐data systems. First, a novel integral inequality with the cubic term of integral interval length instead of reciprocal one of integral interval length is constructed by non‐orthogonal polynomials. This can make full use of slack matrix variables and additional information about sawtooth structural sampling pattern. Then, on the basis of the constructed integral inequality, a cubic‐term‐dependent discontinuous exponent Lyapunov–Krasovskii Functional (LKF) is developed containing additional information about system states to design an sampled‐data state feedback controller. To better estimate the upper bound of the derivative of LKF, a kind of multiple convex function approximation approach is developed, which can be used to deal with the two‐variable polynomial negative definite issue by dividing the variable interval into multiple subintervals. By the constructed integral inequality and multiple convex function approximation approach, sufficient conditions with less conservatism are deduced for the feasibility of sampled‐data state feedback controller. Moreover, by the inner convex approximation solution technique and proposed iterative algorithm, the bilinear matrix inequalities can be transformed into linear matrix ones, which can be easily tackled, to obtain the desired sampled‐data controller gain. Finally, by comparing with existing results, the advantages and superiority of our proposed approaches can be confirmed via two numerical examples.

show abstract

On stability and H_∞ control synthesis of sampled‐data systems: A multiple convex function approximation approach

Ji,

Jiang,

Sun

et al. 2024

Intl J Robust & Nonlinear

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show abstract

Improved stability criteria for sampled-data systems using modified free weighting matrix

Lee

Kwon

Lee

2019

Journal of the Franklin Institute

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Polynomial LPV approach to robust H_∞ control of nonlinear sampled-data systems

Hooshmandi

Bayat

Jahed‐Motlagh

et al. 2018

International Journal of Control

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Cited by 3 publications

References 11 publications

On stability and H_∞ control synthesis of sampled‐data systems: A multiple convex function approximation approach

On stability and H_∞ control synthesis of sampled‐data systems: A multiple convex function approximation approach

Improved stability criteria for sampled-data systems using modified free weighting matrix

Polynomial LPV approach to robust H_∞ control of nonlinear sampled-data systems

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Cited by 3 publications

References 11 publications

On stability and H∞ control synthesis of sampled‐data systems: A multiple convex function approximation approach

On stability and H∞ control synthesis of sampled‐data systems: A multiple convex function approximation approach

Improved stability criteria for sampled-data systems using modified free weighting matrix

Polynomial LPV approach to robust H∞ control of nonlinear sampled-data systems

Contact Info

Product

Resources

About

On stability and H_∞ control synthesis of sampled‐data systems: A multiple convex function approximation approach

On stability and H_∞ control synthesis of sampled‐data systems: A multiple convex function approximation approach

Polynomial LPV approach to robust H_∞ control of nonlinear sampled-data systems