Robust Control for Continuous LPV System with Restricted-Model-Based Control

Maalej, Sonia; Kruszewski, Alexandre; Belkoura, Lotfi

doi:10.1007/s00034-016-0404-6

Cited by 6 publications

(10 citation statements)

References 29 publications

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“…Since the idea of the controller structure is to nullify the system dynamic and then to replace it with the ideal dynamic for the closed loop, we consider the following control law introduced by [13] and represented in Fig.2:…”

Section: The Controller/derivative Conceptionmentioning

confidence: 99%

“…All these studies state that the stability as well as performances are ensured but none of them provides a standard proof on a class of system. Recently, the authors of [12,13] have considered the use of the model-free theory and the polytopic transformation to tackle problems related to the stability tuning method of non-linear systems with time-varying parameters. Easy tuning conditions for the controller parameter guaranteeing the stability are provided.…”

Section: Introductionmentioning

confidence: 99%

“…(i) Proposing a new controller design procedures inspired from our previous work [12,13]. This controller is based on a signal differentiators and dynamic nullification and implemented in a processor based device such that the sensor data are only available at sampling instants.…”

Section: Introductionmentioning

confidence: 99%

“…This paper is organized as follows: The third section summarizes some of the main theoretical ideas which are shaping the model free-control presented by [12,13]. A time-delay approach to deal with sampling effects is proved.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Derivative-Based Sampled Data Control for Continuous Linear Parameter Varying System With Unknown Parameters

Maalej

Kruszewski

Belkoura

2019

Journal of Dynamic Systems, Measurement, and Control

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This paper deals with the robust stabilization of a class of linear parameter varying (LPV) systems in the sampled data control case. Instead of using a state observer or searching for a dynamic output feedback, the considered controller is based on output derivatives estimation. This allows the stabilization of the plant with very large parameter variations or uncertainties. The proof of stability is based on the polytopic representation of the closed-loop under Lyapunov conditions and system transformations. The result is a control structure with only one parameter tuned via very simple conditions. Finally, the effectiveness of the proposed method is verified via a numerical example of a second-order LPV system.

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Section: The Controller/derivative Conceptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Derivative-Based Sampled Data Control for Continuous Linear Parameter Varying System With Unknown Parameters

Maalej

Kruszewski

Belkoura

2019

Journal of Dynamic Systems, Measurement, and Control

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“…Linear parameter varying (LPV) models are widely used in nonlinear control systems [1], [2], [3], [4], [5], [6], [7], [8], [9]. In order to build such models from sensor data, different methods for LPV system identification have been reported [10], [11], [12], [13], [14], [15], [5], [16], [17], [18].…”

Section: Introductionmentioning

confidence: 99%

On Local LTI Model Coherence for LPV Interpolation

Zhang

Ljung

Pintelon

2020

IEEE Trans. Automat. Contr.

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In the local approach to linear parameter varying (LPV) system identification, it is widely acknowledged that locally estimated linear state-space models should be made coherent before being interpolated, but the accurate meaning of the term "coherent" or "coherence" is rarely defined. The purpose of this paper is to analyze the relevance of two existing definitions and to point out the consequence of this analysis on the practice of LPV system identification.

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Energy saving for building heating via a simple and efficient model-free control design: First steps with computer simulations

Abouaïssa

Hasan

Join

et al. 2017

2017 21st International Conference on System Theory, Control and Computing (ICSTCC)

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The model-based control of building heating systems for energy saving encounters severe physical, mathematical and calibration difficulties in the numerous attempts that has been published until now. This topic is addressed here via a new model-free control setting, where the need of any mathematical description disappears. Several convincing computer simulations are presented. Comparisons with classic PI controllers and flatness-based predictive control are provided.

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Robust Control for Continuous LPV System with Restricted-Model-Based Control

Abstract: International audienc

Cited by 6 publications

References 29 publications

Derivative-Based Sampled Data Control for Continuous Linear Parameter Varying System With Unknown Parameters

Derivative-Based Sampled Data Control for Continuous Linear Parameter Varying System With Unknown Parameters

On Local LTI Model Coherence for LPV Interpolation

Energy saving for building heating via a simple and efficient model-free control design: First steps with computer simulations

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