Special issue on linear parameter varying systems

Edwards, Christopher; Marcos, Andrés; Balas, Gary J.

doi:10.1002/rnc.3228

Cited by 11 publications

(6 citation statements)

References 6 publications

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“…Taking advantage of the LQR robustness and availability to MIMO systems such as DFIG [15][16][17], this optimal controller is used to improve the dynamic response, the stability and the robustness of the control system against parameters variations. The authors of [18][19][20][21][22][23] have proposed different LQR control schemes for the considered system. These presented methods are mainly based either on a Linearized Time Invariant (LTI) model or on a small signal model of the system.…”

Section: Introductionmentioning

confidence: 99%

LQR Robust Control for Active and Reactive Power Tracking of a DFIG based WECS

Salhi¹,

Salhi²

2019

ijacsa

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This research work sets forward a new formulation of Linear Quadratic Regulator problem (LQR) applied to a Wind Energy Conversion System (WECS). A new necessary and sufficient condition of Lyapunov asymptotic stability is also established. The problem is mathematically described in form of Linear Matrix Inequalities (LMIs). The considered WECS is based on a Doubly Fed Induction Generator (DFIG). An appropriate Linear Parameter Varying (LPV) model is designed. This model stands for a realistic representation of the randomly time varying wind velocity. Stability and robustness of the controller over the admissible values of time varying parameter are investigated. The newly lifted Lyapunov condition gives less conservative conditions for LMI approach in case of parameterdependent Lyapunov functions PDLF. The considered PDLF has the same variation dynamics as the system matrix. The intrinsic objective for our research is to offer more freedom degrees to the control problem and to improve the efficiency of the controller in case of uncertainties or parametric variations. The performances of the proposed theorems are validated to achieve active and reactive powers tracking of the WECS over the admissible range of wind speeds. The interesting features of the proposed solution are the simpler implementation and the larger robustness margin. It also has the advantage of providing a linear control to the considered nonlinear system without resorting to linearization. The LMIs implementation is performed on Yalmip Matlab toolbox. The proposed controller is verified on a Matlab Simulink emulator. This work presents an extension of the LQR control problem to LPV systems.

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Section: Introductionmentioning

confidence: 99%

LQR Robust Control for Active and Reactive Power Tracking of a DFIG based WECS

Salhi¹,

Salhi²

2019

ijacsa

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“…Linear parameter varying (LPV), as well as linear time varying (LTV), models are valuable alternatives to approximate the behaviour of non‐linear models. They have been successfully used for different control problems, such as aerospace, automotive and renewable energies [13–17]. The LPV framework, first introduced in [18], enhances the modelling capabilities of LTI systems, by describing a family of non‐stationary models where the state‐space depends on a finite number of measurable, exogenous, time‐varying scheduling parameters [19].…”

Section: Introductionmentioning

confidence: 99%

Computationally efficient model predictive control for a class of linear parameter‐varying systems

Cavanini

Cimini²,

Ippoliti

2018

IET Control Theory & Applications

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“…Hence, robust MPC (RMPC) for those non‐ideal systems is of more theoretical and practical significance . One class of systems that take into account the uncertainties are the so‐called linear parameter varying (LPV) systems .…”

Section: Introductionmentioning

confidence: 99%

“…Hence, robust MPC (RMPC) for those non-ideal systems is of more theoretical and practical significance [1,2]. One class of systems that take into account the uncertainties are the so-called linear parameter varying (LPV) systems [3,4].Papers investigating RMPC of LPV systems can be found in [5][6][7], and more recently [8][9][10][11], and so on. The results of these papers were developed based on the assumption that system states are always measurable.…”

mentioning

confidence: 99%

An optimal approach to output-feedback robust model predictive control of LPV systems with disturbances

Yang¹,

Gao²,

Feng

et al. 2016

Int. J. Robust. Nonlinear Control

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Summary An observer‐based output feedback predictive control approach is proposed for linear parameter varying systems with norm‐bounded external disturbances. Sufficient and necessary robust positively invariant set conditions of the state estimation error are developed to determine the minimal ellipsoidal robust positively invariant set and observer gain through offline computation. The quadratic upper bound of state estimation error is updated and included in an ℋ∞‐type cost function of predictive control to optimize transient output feedback control performance. Recursive feasibility of the dynamic convex optimization problem is guaranteed in the proposed predictive control strategy. With the input‐to‐state stable observer, the closed‐loop control system states are steered into a bounded set. Simulation results are given to demonstrate the effectiveness of the proposed control strategy. Copyright © 2016 John Wiley & Sons, Ltd.

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Special issue on linear parameter varying systems

Cited by 11 publications

References 6 publications

LQR Robust Control for Active and Reactive Power Tracking of a DFIG based WECS

LQR Robust Control for Active and Reactive Power Tracking of a DFIG based WECS

Computationally efficient model predictive control for a class of linear parameter‐varying systems

An optimal approach to output-feedback robust model predictive control of LPV systems with disturbances

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