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Journal articles on the topic 'Robust LPV Control'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

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1

Eichler, Annika, Christian Hoffmann, and Herbert Werner. "Robust control of decomposable LPV systems." Automatica 50, no. 12 (2014): 3239–45. http://dx.doi.org/10.1016/j.automatica.2014.10.046.

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2

Shen, Bin, Lingfei Xiao, and Zhifeng Ye. "A Full Envelope Robust Linear Parameter-Varying Control Method for Aircraft Engines." Aerospace 10, no. 9 (2023): 769. http://dx.doi.org/10.3390/aerospace10090769.

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In order to solve the problem of full flight envelope control for aircraft engines, the design of a linear parameter-varying (LPV) controller is described in this paper. First, according to the nonlinear aerodynamic model of the aircraft engine, the LPV engine model for the controller design is obtained through the Jacobian linearization and fitting technique. Then, the flight envelope is divided into several sub-regions, and the intersection of adjacent sub-regions is not empty. The sub-region LPV controller is designed using the parameter-dependent Lyapunov function (PDLF)-based LPV synthesi

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3

Ma, Song Hui, Peng Yuan Shao, and Cheng Fu Wu. "LPV Based Robust Gain – Scheduling Control for Transient Mode of Morphing UAV." Advanced Materials Research 622-623 (December 2012): 1368–72. http://dx.doi.org/10.4028/www.scientific.net/amr.622-623.1368.

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Robust Gain-Scheduling control based on Linear Parameter-Varying (LPV) system is researched in theory and applied to transient mode control of a morphing wing UAV (MUAV). H∞ output feedback control method is extended to the LPV system via parameterized LMIs. In application, LPV model of MUAV is established using the Jacobian linearization method, based on which an LPV controller is designed using the proposed method to control the attitudes of transient mode in morphing process, the problem of high frequency dynamics is found and solved by a robust pole constraint method. Monte-Carlo simulatio

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4

Hasseni, Seif-El-Islam, and Latifa Abdou. "Robust LPV Control for Attitude Stabilization of a Quadrotor Helicopter under Input Saturations." Advances in Technology Innovation 5, no. 2 (2020): 98–111. http://dx.doi.org/10.46604/aiti.2020.3953.

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This article investigates the robust stabilization of the rotational subsystem of a quadrotor against external inputs (disturbances, noises, and parametric uncertainties) by the LFT-based LPV technique. By establishing the LPV attitude model, the LPV robust controller is designed for the system. The weighting functions are computed by Cuckoo Search, a meta-heuristic optimization algorithm. Besides, the input saturations are also taken into account through the Anti-Windup compensation technique. Simulation results show the robustness of the closed-loop system against disturbances, measurement n

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5

Szabó, Z., Zs Biró, and J. Bokor. "All controllers for an LPV robust control problem." IFAC Proceedings Volumes 45, no. 13 (2012): 343–48. http://dx.doi.org/10.3182/20120620-3-dk-2025.00058.

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6

Zhou, Guang Rui, Shi Qian Liu, Yuan Jun Sang, Xu Dong Wang, Xiao Peng Jia, and Er Zhuo Niu. "LPV robust servo control of aircraft active side-sticks." Aircraft Engineering and Aerospace Technology 92, no. 4 (2020): 599–609. http://dx.doi.org/10.1108/aeat-08-2019-0155.

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Purpose This paper aims to focus on the variable stick force-displacement (SFD) gradience in the active side stick (ASS) servo system for the civil aircraft. Design/methodology/approach The problem of variable SFD gradience was introduced first, followed by the analysis of its impact on the ASS servo system. To solve this problem, a linear-parameter-varying (LPV) control approach was suggested to process the variable gradience of the SFD. A H∞ robust control method was proposed to deal with the external disturbance. Findings To validate the algorithm performance, a linear time-variant system w

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7

Cao, Guoyan, Karolos M. Grigoriadis, and Yaw D. Nyanteh. "LPV Control for the Full Region Operation of a Wind Turbine Integrated with Synchronous Generator." Scientific World Journal 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/638120.

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Wind turbine conversion systems require feedback control to achieve reliable wind turbine operation and stable current supply. A robust linear parameter varying (LPV) controller is proposed to reduce the structural loads and improve the power extraction of a horizontal axis wind turbine operating in both the partial load and the full load regions. The LPV model is derived from the wind turbine state space models extracted by FAST (fatigue, aerodynamics, structural, and turbulence) code linearization at different operating points. In order to assure a smooth transition between the two regions,

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8

He, Xing, Wei Jiang, and Caisheng Jiang. "Robust Controller Designing for an Air-Breathing Hypersonic Vehicle with an HOSVD-Based LPV Model." International Journal of Aerospace Engineering 2021 (December 3, 2021): 1–12. http://dx.doi.org/10.1155/2021/7570059.

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This paper focuses on the linear parameter varying (LPV) modeling and controller design for a flexible air-breathing hypersonic vehicle (AHV). Firstly, by selecting the measurable altitude and velocity as gain-scheduled variables, the original longitudinal nonlinear model for AHV is transformed into the LPV model via average gridding division, vertex trimming, Jacobian linearization, and multiple linear regression within the entire flight envelope. Secondly, using the tensor product model transformation method, the obtained LPV model is converted into the polytopic LPV model via high-order sin

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9

Chen, Jianchi, Dawei Gu, Ian Postlethwaite, and Kannan Natesan. "Robust LPV Control of UAV with Parameter Dependent Performance." IFAC Proceedings Volumes 41, no. 2 (2008): 15070–75. http://dx.doi.org/10.3182/20080706-5-kr-1001.02550.

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10

Xie, W. "Robust control system design for polytopic stable LPV systems." IMA Journal of Mathematical Control and Information 20, no. 2 (2003): 201–16. http://dx.doi.org/10.1093/imamci/20.2.201.

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11

Maalej, Sonia, Alexandre Kruszewski, and Lotfi Belkoura. "Robust Control for Continuous LPV System with Restricted-Model-Based Control." Circuits, Systems, and Signal Processing 36, no. 6 (2016): 2499–520. http://dx.doi.org/10.1007/s00034-016-0404-6.

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12

Chen, Fenghua, Xinguo Qiu, Khalid A. Alattas, Ardashir Mohammadzadeh, and Ebrahim Ghaderpour. "A New Fuzzy Robust Control for Linear Parameter-Varying Systems." Mathematics 10, no. 18 (2022): 3319. http://dx.doi.org/10.3390/math10183319.

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The linear parameter-varying (LPV) models have broad applications in advanced mathematics and modern control systems. This paper introduces a new method for controlling the LPV systems. This method includes the gain-scheduled state-feedback technique and a fuzzy system to calculate the state-feedback gain. The main goal of the control system is to stabilize the system and bring its states to equilibrium points. Linear matrix inequalities calculate feedback gains to stabilize the system. On the other hand, a fuzzy control system also produces a combined signal with the primary controller signal

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13

Degtyarev, G. L., R. N. Faizutdinov, and I. O. Spiridonov. "Multiobjective Robust Controller Synthesis for Nonlinear Mechanical System." Mekhatronika, Avtomatizatsiya, Upravlenie 19, no. 11 (2018): 691–98. http://dx.doi.org/10.17587/mau.19.691-698.

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In the paper multiobjective robust controller synthesis problem for nonlinear mechanical system described by Lagrange’s equations of the second kind is considered. Such tasks have numerous practical applications, for example in controller design of robotic systems and gyro-stabilized platforms. In practice, we often have to use uncertain mathematical plant models in controller design. Therefore, ensuring robustness in presence of parameters perturbations and unknown external disturbances is an important requirement for designed systems. Much of modern robust control theory is linear. When the

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14

Dalila, Khamari, Makouf Abdessalem, Drid Said, and Larbi Chrifi-Alaoui. "Robust linear parameter varying induction motor control with polytopic models." Serbian Journal of Electrical Engineering 10, no. 2 (2013): 335–48. http://dx.doi.org/10.2298/sjee121218008d.

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This paper deals with a robust controller for an induction motor which is represented as a linear parameter varying systems. To do so linear matrix inequality (LMI) based approach and robust Lyapunov feedback controller are associated. This new approach is related to the fact that the synthesis of a linear parameter varying (LPV) feedback controller for the inner loop take into account rotor resistance and mechanical speed as varying parameter. An LPV flux observer is also synthesized to estimate rotor flux providing reference to cited above regulator. The induction motor is described as a pol

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15

Jia, Qiusheng, Xinxing Shi, Yan Li, and Huacong LI. "LPV Robust Controller Design with Regional Pole Assignment for an Aero-Engine." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 37, no. 6 (2019): 1248–56. http://dx.doi.org/10.1051/jnwpu/20193761248.

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The aerodynamic characteristics of aero-engine, which have a wide range of flight envelopes, vary drastically, so its controller is required to be able to adapt to a large range of parameter variations and have good robustness. To solve the above problem, based on the regional pole assignment, a new aero-engine multi-variable robust gain scheduled LPV control algorithm was proposed. Firstly, the Jacobian linearization method was used to obtain polynomial LPV model of aero-engine, which can describe its dynamic performance under certain conditions. Further, aiming at the polynomial LPV model, a

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16

Ku, Cheung-Chieh, and Guan-Wei Chen. "H∞Gain-Scheduled Control for LPV Stochastic Systems." Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/854957.

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A robust control problem for discrete-time uncertain stochastic systems is discussed via gain-scheduled control scheme subject toH∞attenuation performance. Applying Linear Parameter Varying (LPV) modeling approach and stochastic difference equation, the uncertain stochastic systems can be described by combining time-varying weighting function and linear systems with multiplicative noise terms. Due to the consideration of stochastic behavior, the stability in the sense of mean square is applied for the system. Furthermore, two kinds of Lyapunov functions are employed to derive their correspondi

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17

Najarzadeh, reza, maryam dehghani, mohammad hassan asemani, and roozbeh abolpour. "Optimal Robust LPV Control Design for Novel Covid-19 Disease." Journal of Control 14, no. 5 (2021): 141–53. http://dx.doi.org/10.52547/joc.14.5.141.

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18

Lee, S. M., S. C. Won, D. H. Ji, and J. H. Park. "Robust model predictive control for LPV systems using relaxation matrices." IET Control Theory & Applications 1, no. 6 (2007): 1567–73. http://dx.doi.org/10.1049/iet-cta:20060525.

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19

Bendtsen, J. D., and K. Trangbaek. "Robust quasi-LPV control based on neural state-space models." IEEE Transactions on Neural Networks 13, no. 2 (2002): 355–68. http://dx.doi.org/10.1109/72.991421.

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20

Liu, Shiqian, Yuanjun Sang, and Hongbin Jin. "Robust model predictive control for stratospheric airships using LPV design." Control Engineering Practice 81 (December 2018): 231–43. http://dx.doi.org/10.1016/j.conengprac.2018.09.007.

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21

Németh, Balázs, Attila Lelkó, and Péter Gáspár. "Robust LPV control synthesis for learning-aided driver assistance systems." IFAC-PapersOnLine 55, no. 35 (2022): 97–102. http://dx.doi.org/10.1016/j.ifacol.2022.11.296.

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22

Schaab, Konstantin, and Olaf Stursberg. "Robust Decentralized LPV Control for Transient Stability of Power Systems." IFAC-PapersOnLine 48, no. 30 (2015): 566–71. http://dx.doi.org/10.1016/j.ifacol.2015.12.440.

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23

Hadian, Mohsen, Amin Ramezani, and Wenjun Zhang. "Robust Model Predictive Controller Using Recurrent Neural Networks for Input–Output Linear Parameter Varying Systems." Electronics 10, no. 13 (2021): 1557. http://dx.doi.org/10.3390/electronics10131557.

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This paper develops a model predictive controller (MPC) for constrained nonlinear MIMO systems subjected to bounded disturbances. A linear parameter varying (LPV) model assists MPC in dealing with nonlinear dynamics. In this study, the nonlinear process is represented by an LPV using past input–output information (LPV-IO). Two primary objectives of this study are to reduce online computational load compared with the existing literature of MPC with an LPV-IO model and to confirm the robustness of the controller in the presence of disturbance. For the first goal, a recurrent neural network (RNN)

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24

Hasseni, Seif-El-Islam, and Latifa Abdou. "Robust LFT-LPV H∞ Control of an Underactuated Inverted Pendulum on a Cart with Optimal Weighting Functions Selection by GA and ES." Acta Mechanica et Automatica 14, no. 4 (2020): 186–97. http://dx.doi.org/10.2478/ama-2020-0027.

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Abstract This article investigates the robust stabilization and control of the inverted pendulum on a cart against disturbances, measurement noises, and parametric uncertainties by the LFT-based LPV technique (Linear-Fractional-Transformation based Linear-Parameter-Varying). To make the applying of the LPV technique possible, the LPV representation of the inverted pendulum on a cart model is developed. Besides, the underactuated constraint of this vehicle is overcome by considering both degrees of freedom (the rotational one and the translational one) in the structure. Moreover, the selection

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25

Su, Khac Huan, Kwankyun Byeon, Wonhee Kim, and Youngwoo Lee. "LPV H∞ Control with an Augmented Nonlinear Observer for Sawyer Motors." Mathematics 10, no. 1 (2021): 18. http://dx.doi.org/10.3390/math10010018.

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This study presents LPV H∞ control with an augmented nonlinear observer (ANOB) to improve both the position and yaw tracking errors for Sawyer motors. The proposed control method consists of the forces and torque modulation scheme, an ANOB, and a Lyapunov-based current controller with the LPV H∞ state feedback controller to guarantee the stability of tracking error dynamics. The ANOB is designed to estimate all the state variables including the position, velocity, current, and disturbance using only position feedback. We propose a vertex expansion technique to solve the influence of the convex

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26

Li, Hongkun, Rui Huang, Yonghui Zhao, and Haiyan Hu. "Maneuver load alleviation for high performance aircraft robust to flight condition variations." Journal of Vibration and Control 25, no. 5 (2018): 1044–57. http://dx.doi.org/10.1177/1077546318810033.

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The design of a robust maneuver load alleviation (MLA) system for a high-performance aircraft is studied in this paper. First, the aeroservoelastic (ASE) models of a high-performance military aircraft in climbing maneuver at varying Mach numbers are established. Then, a linear parameter-varying (LPV) model of the ASE systems is constructed and an [Formula: see text] robust controller is designed based on the LPV model. The robust control is realized via a pair of outboard ailerons to alleviate the wing-root bending moments in the climbing maneuvers. To compensate the loss of performance in the

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27

Bianchi, Fernando D., and Ricardo S. Sánchez-Peña. "Robust identification/invalidation in an LPV framework." International Journal of Robust and Nonlinear Control 20, no. 3 (2009): 301–12. http://dx.doi.org/10.1002/rnc.1430.

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28

Malik, Arshad Habib, Aftab Ahmed Memon, and Feroza Arshad. "Fractional order multi-scheduling parameters based LPV modelling and robust switching H∞ controllers design for steam dump system of nuclear power plant." Mehran University Research Journal of Engineering and Technology 41, no. 2 (2022): 197–207. http://dx.doi.org/10.22581/muet1982.2202.19.

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In this research work, the highly challenging problem of novel modelling and nonlinear control of steam dump system of Pressurized Water Reactor (PWR) type Nuclear Power Plant (NPP) is attempted. The Fractional Order Multi- Scheduling Parameters based Multi-Input Single- Output Linear Parameter Varying (FO-MSP-MISO-LPV) model of Steam Dump System (SDS) is estimated with uncertain dynamics under sudden load variation transients. MSP for uncertain dynamics of SDS in FO framework is the most challenging problem and attempted in a novel fashion for the first time in nuclear industry. Scheduling pa

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29

Yavari, Reza, Saeed Shamaghdari, and Arash Sadeghzadeh. "Robust output-feedback bumpless transfer control of polytopic uncertain LPV systems." European Journal of Control 63 (January 2022): 277–89. http://dx.doi.org/10.1016/j.ejcon.2021.11.006.

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30

GAO, Zhenxing, and Jun FU. "Robust LPV modeling and control of aircraft flying through wind disturbance." Chinese Journal of Aeronautics 32, no. 7 (2019): 1588–602. http://dx.doi.org/10.1016/j.cja.2019.03.029.

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31

Patton, Ron, Lejun Chen, and Supat Klinkhieo. "An LPV pole-placement approach to friction compensation as an FTC problem." International Journal of Applied Mathematics and Computer Science 22, no. 1 (2012): 149–60. http://dx.doi.org/10.2478/v10006-012-0011-z.

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An LPV pole-placement approach to friction compensation as an FTC problemThe concept of combining robust fault estimation within a controller system to achieve active Fault Tolerant Control (FTC) has been the subject of considerable interest in the recent literature. The current study is motivated by the need to develop model-based FTC schemes for systems that have no unique equilibria and are therefore difficult to linearise. Linear Parameter Varying (LPV) strategies are well suited to model-based control and fault estimation for such systems. This contribution involves pole-placement within

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32

Mystkowski, Arkadiusz. "Robust Optimal Control of MAV Based on Linear-Time Varying Decoupled Model Dynamics." Solid State Phenomena 198 (March 2013): 571–76. http://dx.doi.org/10.4028/www.scientific.net/ssp.198.571.

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This paper discusses a nonlinear robust control design procedure to micro air vehicle that uses the singular value (μ) and μ-synthesis technique. The optimal robust control law that combines a linear parameters varying (LPV) of UAV (unmanned aerial vehicle) are realized by using serial connection of the Kestrel autopilot and the Gumstix microprocessor. Thus, the robust control feedback loops, which handle the uncertainty of aerodynamics derivatives, are used to ensure robustness stability of the UAV local dynamics in longitudinal and lateral control directions.

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33

Yang, Xing, Lu Xiong, Bo Leng, Dequan Zeng, and Guirong Zhuo. "Design, Validation and Comparison of Path Following Controllers for Autonomous Vehicles." Sensors 20, no. 21 (2020): 6052. http://dx.doi.org/10.3390/s20216052.

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As one of the core issues of autonomous vehicles, vehicle motion control directly affects vehicle safety and user experience. Therefore, it is expected to design a simple, reliable, and robust path following the controller that can handle complex situations. To deal with the longitudinal motion control problem, a speed tracking controller based on sliding mode control with nonlinear conditional integrator is proposed, and its stability is proved by the Lyapunov theory. Then, a linear parameter varying model predictive control (LPV-MPC) based lateral controller is formulated that the optimizati

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34

Jafar, Adnan, Aamer Iqbal Bhatti, Sarvat M. Ahmad, and Nisar Ahmed. "H∞Optimization-based robust decoupling control algorithm in linear parameter varying systems using Hadamard weighting." Transactions of the Institute of Measurement and Control 41, no. 7 (2018): 1833–48. http://dx.doi.org/10.1177/0142331218788121.

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This article proposes a novel gain scheduled control technique for a class of linear parameter varying (LPV) systems with main emphasis on reducing the cross coupling interaction in dynamics using the Hadamard weight. By employing the Hadamard and the conventional [Formula: see text] performance weighting, an extended [Formula: see text] closed loop norm LPV theorem is derived that involves traditional [Formula: see text] weights for input output shaping control and Hadamard weight for decoupling control. Furthermore, a robust dynamic output feedback gain scheduled control law is designed to s

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35

Lin, Guo Xian, and Wei Xie. "LPV Modeling of Buck Converter and Gain Scheduling Control." Advanced Materials Research 317-319 (August 2011): 1390–93. http://dx.doi.org/10.4028/www.scientific.net/amr.317-319.1390.

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A kind of gain scheduling control is designed for Buck converter. The small signal model of the Buck converter is translated into the Linear Parameter-Varying (LPV) dynamic equation with the load and the line voltage as the scheduled parameters. Based on it, the closed-loop system poles assignment is taken to the specific area with gain scheduled state feedback via linear matrix inequalities (LMIs) technique, the gain scheduled state feedback is designed to regulate the duty cycle of the switch conduction. Compared with robust state feedback control, it has better disturbance rejection perform

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36

Ríos, Héctor, Susana Viridiana Gutiérrez Martínez, Tarek Raïssi, and Denis Efimov. "An Integral Sliding–Mode–based Interval Predictive Control for Constrained LPV Systems." Memorias del Congreso Nacional de Control Automático 6, no. 1 (2023): 103–8. http://dx.doi.org/10.58571/cnca.amca.2023.011.

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This paper presents the design of a robust controller, based on an integral sliding–mode control (ISMC) approach together with an interval predictor–based state feedback controller and a Model Predictive Control (MPC) scheme, for a class of uncertain linear parameter-varying (LPV) systems. The proposed controller deals with some state and input constraints and is robust to some external disturbances and parameter uncertainties. Furthermore, the performance of the proposed scheme is validated by numerical simulations.

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37

Wen, Nuan, Zhenghua Liu, Yang Sun, and Lingpu Zhu. "Design of LPV-Based Sliding Mode Controller with Finite Time Convergence for a Morphing Aircraft." International Journal of Aerospace Engineering 2017 (2017): 1–20. http://dx.doi.org/10.1155/2017/8426348.

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This paper proposes a finite time convergence sliding mode control (FSMC) strategy based on linear parameter-varying (LPV) methodology for the stability control of a morphing aircraft subject to parameter uncertainties and external disturbances. Based on the Kane method, a longitudinal dynamic model of the morphing aircraft is built. Furthermore, the linearized LPV model of the aircraft in the wing transition process is obtained, whose scheduling parameters are wing sweep angle and wingspan. The FSMC scheme is developed into LPV systems by applying the previous results for linear time-invarian

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38

Shen, Yuan Chuan, Jian Qiao Yu, Guan Chen Luo, and Rui Guang Yang. "Robust Gain-Scheduling Controller for Airbreathing Hypersonic Flight Vehicle." Applied Mechanics and Materials 716-717 (December 2014): 1624–30. http://dx.doi.org/10.4028/www.scientific.net/amm.716-717.1624.

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This paper addresses issues related to robust control for an airbreathing hypersonic flight vehicle. Owing to aero-propulsion couplings caused by the unique structure shape, the model of the vehicle is greatly nonlinear and complex, which presents an enormous technical challenge for control. The nonlinear model is transformed into a linear fractional transformation (LFT) model, and a robust gain-scheduling controller based on linear parameter-varying control (LPV) with full block multipliers is obtained. Simulations illustrate great improvements of the dynamic performance in closed-loop system

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39

Gao, Zhen Bin. "A LPV Network Control System Fault Detection Based on H_∞ Control Theory." Applied Mechanics and Materials 568-570 (June 2014): 1085–89. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.1085.

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This paper considers the problem of a polytopic approach for Linear parameter Variation network control system with the sensor failure case. Based on Bounded Real Lemma of control theory, the sufficient condition of robust stability of a LPV augmented network control system with tracking error and the sensor failure is addressed; Using Linear Matrix Inequality convex optimal technique, the feasible solution of state feedback controller is obtained. The simulation of a inverted pendulum model shows that the presented method is feasible and effective.

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40

Saeed, Azmat, Aamer I. Bhatti, and Fahad M. Malik. "LMIs-Based LPV Control of Quadrotor with Time-Varying Payload." Applied Sciences 13, no. 11 (2023): 6553. http://dx.doi.org/10.3390/app13116553.

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Applications of a quadrotor with payload, particularly for chemical spraying, have increased in recent times. The variation in payload mass over time causes a change in the moments of inertia (MOI). Moreover, large tilt angles are required for fast reference tracking and external disturbance rejection. These variations in plant parameters (i.e., mass and inertia) and large tilt angles can degrade the control scheme’s performance and stability. This article proposes a linear matrix inequalities (LMIs)-based linear parameter varying (LPV) control scheme for a quadrotor subject to time-varying ma

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41

Song, Lei, and Jianying Yang. "Robust reliable tracking controller design against actuator faults for LPV systems." Asian Journal of Control 13, no. 6 (2010): 1075–81. http://dx.doi.org/10.1002/asjc.286.

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42

Rotondo, Damiano, Fatiha Nejjari, and Vicenç Puig. "Robust state-feedback control of uncertain LPV systems: An LMI-based approach." Journal of the Franklin Institute 351, no. 5 (2014): 2781–803. http://dx.doi.org/10.1016/j.jfranklin.2014.01.018.

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43

Mirzaee, Alireza, Maryam Dehghani, and Mohsen Mohammadi. "Robust LPV control design for blood glucose regulation considering daily life factors." Biomedical Signal Processing and Control 57 (March 2020): 101830. http://dx.doi.org/10.1016/j.bspc.2019.101830.

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44

Hooshmandi, Kaveh, Farhad Bayat, Mohammad Reza Jahed-Motlagh, and Ali Akbar Jalali. "Polynomial LPV approach to robust H ∞ control of nonlinear sampled-data systems." International Journal of Control 93, no. 9 (2018): 2145–60. http://dx.doi.org/10.1080/00207179.2018.1547422.

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45

Buzachero, Luiz F. S., Edvaldo Assunção, Marcelo C. M. Teixeira, and Emerson R. P. da Silva. "Switched Optimized Robust Control of Uncertain LPV Systems Subject to Structural Faults." IFAC-PapersOnLine 51, no. 25 (2018): 353–58. http://dx.doi.org/10.1016/j.ifacol.2018.11.132.

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46

Theißen, Moritz, Konstantin Schaab, and Olaf Stursberg. "Voltage Stability of Power Grids with PV Plants using Robust LPV-Control." IFAC-PapersOnLine 49, no. 27 (2016): 54–59. http://dx.doi.org/10.1016/j.ifacol.2016.10.719.

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Schaab, Konstantin, and Olaf Stursberg. "Decentralized Robust Control of Power Grids Using LPV-Models of DAE-Systems." IFAC-PapersOnLine 48, no. 26 (2015): 218–23. http://dx.doi.org/10.1016/j.ifacol.2015.11.140.

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Németh, Balázs. "Providing Guaranteed Performances for an Enhanced Cruise Control Using Robust LPV Method." Acta Polytechnica Hungarica 20, no. 7 (2023): 133–52. http://dx.doi.org/10.12700/aph.20.7.2023.7.8.

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Rios-Bolivar, Addison, and Francklin Rivas. "Designing a Generalized PIO for Polytropic Discrete Time Systems." EQUATIONS 1 (January 1, 2021): 1–10. http://dx.doi.org/10.37394/232021.2021.1.1.

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Abstract:

Considering the Linear Parameter Varying (LPV) systems of discrete time, in this paper an approach for the synthesis of robust Proporcional+Integral Observers (PIO) is presented. From LPV systems characterized with polytopical uncertainties, the method of design is based on considering a dynamics extended of the typical PIO, in order to transform the design of the matrices of the dynamics of the observer, as a design of the gain of Static Output Feedback (SOF) of a problem of robust control. Under these conditions and from the norms H2=H1 described as Linear Matrix Inequalities (LMI), the crit

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Aouani, Nedia, and Carlos Olalla. "Robust LQR Control for PWM Converters with Parameter-Dependent Lyapunov Functions." Applied Sciences 10, no. 21 (2020): 7534. http://dx.doi.org/10.3390/app10217534.

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Abstract:

This paper presents a novel framework for robust linear quadratic regulator (LQR)-based control of pulse-width modulated (PWM) converters. The converter is modeled as a linear parameter-varying (LPV) system and the uncertainties, besides their rate of change, are taken into account. The proposed control synthesis method exploits the potential of linear matrix inequalities (LMIs), assuring robust stability whilst obtaining non-conservative results. The method has been validated in a PWM DC–DC boost converter, such that it has been shown, with the aid of simulations, that improved robustness and

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