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Journal articles on the topic 'Quasi-LPV Systems'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

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1

Pérez-Estrada, A. J., G. L. Osorio-Gordillo, M. Darouach, and V. H. Olivares-Peregrino. "Generalized dynamic observer design for quasi-LPV systems." at - Automatisierungstechnik 66, no. 3 (2018): 225–33. http://dx.doi.org/10.1515/auto-2017-0060.

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Abstract This paper presents a new generalized dynamic observer (GDO) for quasi-linear parameter varying (LPV) systems. It generalises the structures of the proportional observer (PO) and proportional integral observer (PIO). The design of the GDO is derived from the solution of linear matrix inequalities (LMIs) and the solution of the algebraic constraints obtained from the estimation error analysis. The efficiency of the proposed approach is illustrated by a numerical example.

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2

Lu, Yaohui, and Yaman Arkun. "Quasi-Min-Max MPC algorithms for LPV systems." Automatica 36, no. 4 (2000): 527–40. http://dx.doi.org/10.1016/s0005-1098(99)00176-4.

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3

Grimble, M. J., Pawel Majecki, and M. R. Katebi. "Extended NGMV Predictive Control of Quasi-LPV Systems." IFAC-PapersOnLine 50, no. 1 (2017): 4101–7. http://dx.doi.org/10.1016/j.ifacol.2017.08.795.

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4

Robles, Ruben, Antonio Sala, and Miguel Bernal. "Performance-oriented quasi-LPV modeling of nonlinear systems." International Journal of Robust and Nonlinear Control 29, no. 5 (2018): 1230–48. http://dx.doi.org/10.1002/rnc.4444.

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5

Wang, Xiao Ming, Alois Steiner, and Jan Fiala. "Linear Parameter-Varying Modeling of Electric Vehicle Air Conditioning System." Applied Mechanics and Materials 148-149 (December 2011): 318–25. http://dx.doi.org/10.4028/www.scientific.net/amm.148-149.318.

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This article presents the approach of quasi LPV (Linear Parameter-Varying) modeling techniques for an air conditioning system of an electric vehicle. Vehicle air conditioning systems are strongly non-linear systems and it is a challenging task to get a precise real time model for control purposes. Therefore, an LPV method is first introduced to estimate the air conditioning system. Experimental results show that the LPV model delivers a very high accuracy for the COP (Coefficient Of Performance) estimation, that can’t be reached by traditional identification methods. Some discussion about the

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6

Polat, İ., İ. E. Köse, and E. Eşkinat. "Dynamic output feedback control of quasi-LPV mechanical systems." IET Control Theory & Applications 1, no. 4 (2007): 1114–21. http://dx.doi.org/10.1049/iet-cta:20060326.

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7

Oehlschlägel, Thimo, Christian Heise, Stephan Theil, and Thomas Steffen. "Stability Analysis of Closed Loops of non-linear Systems and LPV Controllers designed using approximated Quasi-LPV Systems." IFAC Proceedings Volumes 45, no. 13 (2012): 349–54. http://dx.doi.org/10.3182/20120620-3-dk-2025.00165.

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8

Coutinho, Pedro H. S., Márcia L. C. Peixoto, Miguel Bernal, Anh-Tu Nguyen, and Reinaldo M. Palhares. "Local Sampled-Data Gain-Scheduling Control of quasi-LPV Systems." IFAC-PapersOnLine 54, no. 4 (2021): 86–91. http://dx.doi.org/10.1016/j.ifacol.2021.10.015.

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9

Huang, Hua, De Feng He, and Qiu Xia Chen. "Quasi-min-max dynamic output feedback MPC for LPV systems." International Journal of System Control and Information Processing 1, no. 3 (2014): 233. http://dx.doi.org/10.1504/ijscip.2014.059675.

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10

Arezki, H., A. Alessandri, and A. Zemouche. "Robust Moving-Horizon Estimation for Quasi-LPV Discrete-Time Systems*." IFAC-PapersOnLine 56, no. 2 (2023): 6771–76. http://dx.doi.org/10.1016/j.ifacol.2023.10.384.

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11

Machala, Dawid, Simona Dobre, Marie Albisser, Floriane Collin, and Marion Gilson. "Quasi-LPV modelling of a projectile’s behaviour in flight." IFAC-PapersOnLine 51, no. 15 (2018): 1080–85. http://dx.doi.org/10.1016/j.ifacol.2018.09.050.

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12

Ding, Baocang, Xubin Ping, and Hongguang Pan. "On dynamic output feedback robust MPC for constrained quasi-LPV systems." International Journal of Control 86, no. 12 (2013): 2215–27. http://dx.doi.org/10.1080/00207179.2013.809796.

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13

Pérez-Estrada, A. J., G. L. Osorio-Gordillo, M. Darouach, M. Alma, and V. H. Olivares-Peregrino. "Generalized dynamic observers for quasi-LPV systems with unmeasurable scheduling functions." International Journal of Robust and Nonlinear Control 28, no. 17 (2018): 5262–78. http://dx.doi.org/10.1002/rnc.4309.

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14

López-Estrada, Francisco-Ronay, Damiano Rotondo, and Guillermo Valencia-Palomo. "A Review of Convex Approaches for Control, Observation and Safety of Linear Parameter Varying and Takagi-Sugeno Systems." Processes 7, no. 11 (2019): 814. http://dx.doi.org/10.3390/pr7110814.

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This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniqu

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15

Grimble, Mike J., and Pawel Majecki. "Observer Based Restricted Structure Generalized Predictive Control for quasi-LPV Nonlinear Systems." IFAC-PapersOnLine 53, no. 2 (2020): 4264–71. http://dx.doi.org/10.1016/j.ifacol.2020.12.2480.

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16

Alessandri, A., M. Zasadzinski, and A. Zemouche. "Optimistic vs Pessimistic Moving-Horizon Estimation for Quasi–LPV Discrete-Time Systems." IFAC-PapersOnLine 53, no. 2 (2020): 5004–9. http://dx.doi.org/10.1016/j.ifacol.2020.12.1096.

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17

Meng Zhao, Canchen Jiang, Xiaoming Tang, and Minghong She. "Interpolation Model Predictive Control of Nonlinear Systems Described by Quasi-LPV Model." Automatic Control and Computer Sciences 52, no. 5 (2018): 354–64. http://dx.doi.org/10.3103/s0146411618050085.

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18

Coutinho, Pedro H. S., Márcia L. C. Peixoto, Iury Bessa, and Reinaldo Martinez Palhares. "Dynamic event-triggered gain-scheduling control of discrete-time quasi-LPV systems." Automatica 141 (July 2022): 110292. http://dx.doi.org/10.1016/j.automatica.2022.110292.

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19

Dehak, Amine, Anh-Tu Nguyen, Antoine Dequidt, Laurent Vermeiren, and Michel Dambrine. "A Reduced-Complexity Polytopic Control Approach for Uncertain quasi-LPV Descriptor Systems." IFAC-PapersOnLine 56, no. 2 (2023): 2176–81. http://dx.doi.org/10.1016/j.ifacol.2023.10.1124.

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20

Cisneros, Pablo S. G., Adwait Datar, Patrick Göttsch, and Herbert Werner. "Data-Driven quasi-LPV Model Predictive Control Using Koopman Operator Techniques." IFAC-PapersOnLine 53, no. 2 (2020): 6062–68. http://dx.doi.org/10.1016/j.ifacol.2020.12.1676.

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21

Cisneros, Pablo S. G., and Herbert Werner. "Wide Range Stabilization of a Pendubot using quasi-LPV Predictive Control." IFAC-PapersOnLine 52, no. 28 (2019): 164–69. http://dx.doi.org/10.1016/j.ifacol.2019.12.367.

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22

Cisneros, Pablo S. G., Aadithyan Sridharan, and Herbert Werner. "Constrained Predictive Control of a Robotic Manipulator using quasi-LPV Representations." IFAC-PapersOnLine 51, no. 26 (2018): 118–23. http://dx.doi.org/10.1016/j.ifacol.2018.11.158.

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23

Ping, Xubin, and Ning Sun. "Dynamic Output Feedback Robust Model Predictive Control via Zonotopic Set-Membership Estimation for Constrained Quasi-LPV Systems." Journal of Applied Mathematics 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/875850.

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For the quasi-linear parameter varying (quasi-LPV) system with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC) is investigated. The estimation error set is represented by a zonotope and refreshed by the zonotopic set-membership estimation method. By properly refreshing the estimation error set online, the bounds of true state at the next sampling time can be obtained. Furthermore, the feasibility of the main optimization problem at the next sampling time can be determined at the current time. A numerical example is given to illustra

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24

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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25

Coutinho, Pedro Henrique Silva, and Reinaldo Martínez Palhares. "Dynamic periodic event-triggered gain-scheduling control co-design for quasi-LPV systems." Nonlinear Analysis: Hybrid Systems 41 (August 2021): 101044. http://dx.doi.org/10.1016/j.nahs.2021.101044.

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26

Rahmanian, Farnoosh, and Mohammad Hassan Asemani. "Quasi-LPV positive observer-based control of closed-loop deep brain stimulation systems." Biomedical Signal Processing and Control 86 (September 2023): 105238. http://dx.doi.org/10.1016/j.bspc.2023.105238.

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27

Kim, Tae-Hyoung, and Ho-Woon Lee. "Quasi-min-max output-feedback model predictive control for LPV systems with input saturation." International Journal of Control, Automation and Systems 15, no. 3 (2017): 1069–76. http://dx.doi.org/10.1007/s12555-016-0378-y.

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28

Bianchi, F. D., R. J. Mantz, and C. F. Christiansen. "Gain scheduling control of variable-speed wind energy conversion systems using quasi-LPV models." Control Engineering Practice 13, no. 2 (2005): 247–55. http://dx.doi.org/10.1016/j.conengprac.2004.03.006.

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29

Park, Jee-Hun, Tae-Hyoung Kim, and Toshiharu Sugie. "Output feedback model predictive control for LPV systems based on quasi-min–max algorithm." Automatica 47, no. 9 (2011): 2052–58. http://dx.doi.org/10.1016/j.automatica.2011.06.015.

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30

Goyal, Jitendra Kumar, Shubham Aggarwal, Sandip Ghosh, Shyam Kamal, and Pawel Dworak. "Quasi‐LPV PI control of TRMS subject to actuator saturation." IET Control Theory & Applications 14, no. 19 (2020): 3157–67. http://dx.doi.org/10.1049/iet-cta.2020.0361.

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31

Cisneros, Pablo Gonzalez, and Herbert Werner. "Fast Nonlinear MPC for Reference Tracking Subject to Nonlinear Constraints via Quasi-LPV Representations." IFAC-PapersOnLine 50, no. 1 (2017): 11601–6. http://dx.doi.org/10.1016/j.ifacol.2017.08.1650.

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32

Hu, Jianchen, and Baocang Ding. "An off-line output feedback MPC strategy for nonlinear systems represented by quasi-LPV model." IFAC-PapersOnLine 51, no. 20 (2018): 66–71. http://dx.doi.org/10.1016/j.ifacol.2018.10.176.

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33

Rotondo, Damiano, Fatiha Nejjari, and Vicenç Puig. "Quasi-LPV modeling, identification and control of a twin rotor MIMO system." Control Engineering Practice 21, no. 6 (2013): 829–46. http://dx.doi.org/10.1016/j.conengprac.2013.02.004.

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34

Xiong, Junfeng, Decai Li, Yuqing He, Feng Gu, and Jianda Han. "Active Quasi-LPV Modeling and Identification for a Water-Jet Propulsion USV: An Experimental Study." IFAC-PapersOnLine 48, no. 28 (2015): 1359–64. http://dx.doi.org/10.1016/j.ifacol.2015.12.321.

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35

Su, Yang, and Kok Kiong Tan. "Comments on “Output feedback model predictive control for LPV systems based on quasi-min–max algorithm”." Automatica 48, no. 9 (2012): 2385. http://dx.doi.org/10.1016/j.automatica.2012.06.100.

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36

Fouka, Majda, Chouki Sentouh, and Jean-Christophe Popieul. "Quasi-LPV Interconnected Observer Design for Full Vehicle Dynamics Estimation With Hardware Experiments." IEEE/ASME Transactions on Mechatronics 26, no. 4 (2021): 1763–72. http://dx.doi.org/10.1109/tmech.2021.3074743.

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37

Rotondo, Damiano, Fatiha Nejjari, and Vicenç Puig. "Robust Quasi–LPV Model Reference FTC of a Quadrotor Uav Subject to Actuator Faults." International Journal of Applied Mathematics and Computer Science 25, no. 1 (2015): 7–22. http://dx.doi.org/10.1515/amcs-2015-0001.

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Abstract A solution for fault tolerant control (FTC) of a quadrotor unmanned aerial vehicle (UAV) is proposed. It relies on model reference-based control, where a reference model generates the desired trajectory. Depending on the type of reference model used for generating the reference trajectory, and on the assumptions about the availability and uncertainty of fault estimation, different error models are obtained. These error models are suitable for passive FTC, active FTC and hybrid FTC, the latter being able to merge the benefits of active and passive FTC while reducing their respective dr

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38

Pagar, Nikhil, Atul Kelkar, and Javad Mohammadpour Velni. "Physics-informed Learning and Control of Nonlinear Systems in Quasi-LPV Framework: An Extended Lagrangian-based Approach." IFAC-PapersOnLine 58, no. 28 (2024): 102–7. https://doi.org/10.1016/j.ifacol.2024.12.018.

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39

Ping, Xubin, Bo Qian, and Ning Sun. "Dynamic Output Feedback Robust MPC with Input Saturation Based on Zonotopic Set-Membership Estimation." Mathematical Problems in Engineering 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/5292375.

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For quasi-linear parameter varying (quasi-LPV) systems with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC) with the consideration of input saturation is investigated. The saturated dynamic output feedback controller is represented by a convex hull involving the actual dynamic output controller and an introduced auxiliary controller. By taking both the actual output feedback controller and the auxiliary controller with a parameter-dependent form, the main optimization problem can be formulated as convex optimization. The considerati

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40

Gómez-Peñate, S., F. R. López-Estrada, G. Valencia-Palomo, D. Rotondo, and J. Enríquez-Zárate. "Actuator and sensor fault estimation based on a proportional-integral quasi-LPV observer with inexact scheduling parameters." IFAC-PapersOnLine 52, no. 28 (2019): 100–105. http://dx.doi.org/10.1016/j.ifacol.2019.12.355.

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41

Srinivasarengan, Krishnan, José Ragot, Christophe Aubrun, and Didier Maquin. "An adaptive observer design approach for a class of discrete-time nonlinear systems." International Journal of Applied Mathematics and Computer Science 28, no. 1 (2018): 55–67. http://dx.doi.org/10.2478/amcs-2018-0004.

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AbstractWe consider the problem of joint estimation of states and some constant parameters for a class of nonlinear discrete-time systems. This class contains systems that could be transformed into a quasi-LPV (linear parameter varying) polytopic model in the Takagi-Sugeno (T-S) form. Such systems could have unmeasured premise variables, a case usually overlooked in the observer design literature. We assert that, for such systems in discrete-time, the current literature lacks design strategies for joint state and parameter estimation. To this end, we adapt the existing literature on continuous

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42

Yassuda, Julio Yuzo, Cristiano Marcos Agulhari, and Emerson Ravazzi Pires da Silva. "Sampled-data robust control of a 2-DoF helicopter modeled using a quasi-LPV framework." Control Engineering Practice 145 (April 2024): 105870. http://dx.doi.org/10.1016/j.conengprac.2024.105870.

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43

Mattei, Massimiliano. "An LPV approach to the robust control of a class of quasi-linear propagation processes." Journal of Process Control 14, no. 6 (2004): 651–60. http://dx.doi.org/10.1016/j.jprocont.2004.01.001.

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44

Wei, Xiukun, and Luigi Del Re. "ON PERSISTENT EXCITATION FOR PARAMETER ESTIMATION OF QUASI-LPV SYSTEMS AND ITS APPLICATION IN MODELING OF DIESEL ENGINE TORQUE." IFAC Proceedings Volumes 39, no. 1 (2006): 517–22. http://dx.doi.org/10.3182/20060329-3-au-2901.00079.

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45

Kien Vu Ngoc. "Efficiency of Robust Observer Design in Power-Assisted Wheelchair Applications." Power System Technology 48, no. 2 (2024): 1977–88. http://dx.doi.org/10.52783/pst.771.

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Unlike manual wheelchairs, power-assisted wheelchairs feature a unique design that allows users to combine their own propulsion with the assistive system. Recently, various studies have concentrated on the control systems for power-assisted wheelchairs. This paper introduces a 2 step control design utilizing a quasi Linear Parameter Varying (LPV) to tackle this complex control problem. The first step involves designing an observer for state and unknown input estimation. The next step proposes a controller to manage parameter including positive gains and input of the system. The control procedu

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46

Inoue, Roberto S., Adriano A. G. Siqueira, and Marco H. Terra. "Experimental results on the nonlinear∞control via quasi-LPV representation and game theory for wheeled mobile robots." Robotica 27, no. 4 (2009): 547–53. http://dx.doi.org/10.1017/s0263574708004931.

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SUMMARYIn this paper, nonlinear dynamic equations of a wheeled mobile robot are described in the state-space form where the parameters are part of the state (angular velocities of the wheels). This representation, known as quasi-linear parameter varying, is useful for control designs based on nonlinear∞approaches. Two nonlinear∞controllers that guarantee induced2-norm, between input (disturbances) and output signals, bounded by an attenuation level γ, are used to control a wheeled mobile robot. These controllers are solved via linear matrix inequalities and algebraic Riccati equation. Experime

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47

Cao, Yong-Yan, and Anke Xue. "Comments on “Quasi-min–max MPC algorithm for LPV systems” by Y. Lu and Y. Arkun, Automatica 36 (2000) 527–540." Automatica 40, no. 7 (2004): 1281–82. http://dx.doi.org/10.1016/j.automatica.2003.10.026.

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48

CAO, Y. "Comments on ?Quasi-min?max MPC algorithm for LPV systems? by Y. Lu and Y. Arkun, Automatica 36 (2000) 527$ndash;540." Automatica 40, no. 7 (2004): 1281–82. http://dx.doi.org/10.1016/s0005-1098(04)00065-2.

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49

Su, Yang, Kok Kiong Tan, and Tong Heng Lee. "Tube based Quasi-min-max Output Feedback MPC for LPV Systems1." IFAC Proceedings Volumes 45, no. 15 (2012): 186–91. http://dx.doi.org/10.3182/20120710-4-sg-2026.00010.

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50

Lim, Jihoon, Patrick Kirchen, and Ryozo Nagamune. "LPV Controller Design for Diesel Engine SCR Aftertreatment Systems based on Quasi-LPV Models." IEEE Control Systems Letters, 2020, 1. http://dx.doi.org/10.1109/lcsys.2020.3046447.

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