Polynomial LPV approach to robust <i>H</i><sub>∞</sub> control of nonlinear sampled-data systems

Hooshmandi, Kaveh; Bayat, Farhad; Jahed‐Motlagh, Mohammad Reza; Jalali, Ali

doi:10.1080/00207179.2018.1547422

Cited by 16 publications

(27 citation statements)

References 61 publications

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“…The problem of the analytical calculation of the maximum allowable sampling period has been recently studied in the context of sampled-data control systems (see e.g. Hooshmandi et al (2018a,b)). A general rule is to choose the sampling frequency greater than (at least two times) the frequency of the fastest mode in the continuous-time system.…”

Section: Simulation Resultsmentioning

confidence: 99%

Wind turbines power regulation using a low-complexity linear parameter varying-model predictive control approach

Bahmani

Bayat

Golchin

2019

Transactions of the Institute of Measurement and Control

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In this paper, the model predictive control (MPC) approach is utilized to stabilize the output power of the wind turbines at the region above the rated wind speed. The controller is designed based on two different approaches and results have been compared. First, by putting the advantages of the MPC approach into practice, the optimal output power regulation of the wind turbine is obtained using a control oriented linear parameter varying (LPV) model of the wind turbine. However, this method inherently requires high computational cost and thus powerful hardware and processors. To cope with this limitation, an efficient suboptimal approach is proposed that significantly reduces the online computational complexity of the controller. In this approach, the main part of the controller design procedure is done off-line prior to the closed-loop wind turbine power generation and a set of optimal controllers were designed using the MPC scheme. Then, a convex combination of the calculated controllers is used for online power regulation of the wind turbine. It is noted that the selected wind turbine is a horizontal axis wind turbine operating at various speeds ranging from 10-25 m/s. Finally, using a set of simulation results we investigate the performance of the proposed approach.

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Section: Simulation Resultsmentioning

confidence: 99%

Wind turbines power regulation using a low-complexity linear parameter varying-model predictive control approach

Bahmani

Bayat

Golchin

2019

Transactions of the Institute of Measurement and Control

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“…The mentioned lemma has been frequently utilized in many works like Apkarian et al (1995), Hooshmandi et al (2018) and Nejem et al (2019) to achieve desired H ∞ controllers for LPV systems.…”

Section: Model Of the Quadrotormentioning

confidence: 99%

Robust linear parameter varying attitude control of a quadrotor unmanned aerial vehicle with state constraints and input saturation subject to wind disturbance

Soltanpour

Hasanvand

Hooshmand

2019

Transactions of the Institute of Measurement and Control

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In this paper, a gain scheduled [Formula: see text] state-feedback controller has been designed to control the attitude of a linear parameter varying (LPV) model of a quadrotor unmanned aerial vehicle (UAV). The scheduling parameters vector, which consists of some states and the control inputs, must vary in a specified polyhedron so that the affine LPV model would be analyzable; therefore, some pre-assumed constraints on states and input saturation have been taken into account in design process. The stabilization and disturbance attenuation conditions are obtained via elementary manipulations on the notion of [Formula: see text] control design. The resulting parameter dependent linear matrix inequalities are solved through a Robust LMI Parser (Rolmip) – which works jointly with YALMIP (A toolbox for modeling and optimization in MATLAB)– by transforming polynomial parameter dependent matrices into multi-simplex domain, to best deal with nonconvex problems. In the end, simulation results have been presented and compared with existing literature to examine the capability of such method in the presence and absence of wind disturbances.

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“…Consequently, much consideration has been given to the stabilization and tracking control of these systems . Several control methods such as output‐feedback control, fuzzy control, L 2 − L ∞ ‐based control, H ∞ ‐based control, Lyapunov‐based approach, and sliding mode control (SMC) have been considered in designing suitable stabilizers and trackers for descriptor/singular systems with time delays.…”

Section: Introductionmentioning

confidence: 99%

Robust global controller design for discrete‐time descriptor systems with multiple time‐varying delays

Mobayen

Bayat

Omidvar

et al. 2020

Intl J Robust & Nonlinear

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Descriptor systems are ubiquitous in many complex practical systems including spacecraft, electrical networks, economic systems, robotic, vibrational, and structural systems. Time delays are ubiquitous in those complex systems. If not addressed properly at the control design stage, they will result in singularities such as oscillation, instability, degraded performance. This article proposes a novel linear matrix inequality (LMI)-based global sliding mode control (GSMC) approach for uncertain discrete-time descriptor systems with multiple time-varying delays. Strict LMI conditions are established based on free-weighting matrices and the Lyapunov-Krasovskii functional to guarantee admissible closed-loop dynamics, that is, regular, causal, and stable. The sufficient condition for the asymptotic stability of the sliding mode dynamics is obtained based on the Lyapunov stability theorem and LMI constraint. The GSMC approach is then formulated based on a global sliding surface to ensure robust performance of the closed-loop system against parametric uncertainties and time delays, while eliminating the reaching phase. The global sliding surface ensures robust performance without the need for a reaching phase, thus establishing sliding around the surface right from the beginning and reducing the control effort. The effectiveness and validity of the proposed approach is assessed using a numerical example. K E Y W O R D Sdiscrete-time descriptor systems, global sliding mode control, LMI, multiple time-varying delay, parametric uncertainties

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

Cited by 16 publications

References 61 publications

Wind turbines power regulation using a low-complexity linear parameter varying-model predictive control approach

Wind turbines power regulation using a low-complexity linear parameter varying-model predictive control approach

Robust linear parameter varying attitude control of a quadrotor unmanned aerial vehicle with state constraints and input saturation subject to wind disturbance

Robust global controller design for discrete‐time descriptor systems with multiple time‐varying delays

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

Cited by 16 publications

References 61 publications

Wind turbines power regulation using a low-complexity linear parameter varying-model predictive control approach

Wind turbines power regulation using a low-complexity linear parameter varying-model predictive control approach

Robust linear parameter varying attitude control of a quadrotor unmanned aerial vehicle with state constraints and input saturation subject to wind disturbance

Robust global controller design for discrete‐time descriptor systems with multiple time‐varying delays

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