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Autore: Grafiati

Pubblicato: 1 giugno 2024

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1

Eichler, Annika, Christian Hoffmann e Herbert Werner. "Robust control of decomposable LPV systems". Automatica 50, n. 12 (dicembre 2014): 3239–45. http://dx.doi.org/10.1016/j.automatica.2014.10.046.

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2

Shen, Bin, Lingfei Xiao e Zhifeng Ye. "A Full Envelope Robust Linear Parameter-Varying Control Method for Aircraft Engines". Aerospace 10, n. 9 (31 agosto 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 synthesis method, while eliminating the dependence of the LPV controller on scheduling parameter derivatives. In order to ensure the stability and performance of the aircraft engine across the full flight envelope, a mixing LPV control method is proposed to design the LPV controller in the overall region. The effectiveness of the proposed method is verified by simulating a dual-spool turbofan engine on a nonlinear component level model and comparing the proposed method with the gain scheduling based on PI and H∞ point design.

3

Ma, Song Hui, Peng Yuan Shao e Cheng Fu Wu. "LPV Based Robust Gain – Scheduling Control for Transient Mode of Morphing UAV". Advanced Materials Research 622-623 (dicembre 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 simulation is performed for 30 times, by which satisfactory performance and robustness of the LPV controller is revealed.

4

Hasseni, Seif-El-Islam, e Latifa Abdou. "Robust LPV Control for Attitude Stabilization of a Quadrotor Helicopter under Input Saturations". Advances in Technology Innovation 5, n. 2 (1 aprile 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 noises, and the parametric uncertainties.

5

Szabó, Z., Zs Biró e J. Bokor. "All controllers for an LPV robust control problem". IFAC Proceedings Volumes 45, n. 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 e Er Zhuo Niu. "LPV robust servo control of aircraft active side-sticks". Aircraft Engineering and Aerospace Technology 92, n. 4 (31 marzo 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 was calculated to be used to worst cases and the SFD gradience was set to linear and non-linear variation to test the algorithm, and some typical examples of pitch angle and side-slip angle tracking control for a large civil aircraft were also used to verify the algorithm. The results showed that the LPV control method had less settling time and less steady tracking errors than H∞ control, even in the variable SFD case. Practical implications This paper presented an ASS servo system using the LPV control method to solve the problem caused by the variable SFD gradience. The motor torque command was calculated by pressure and position feedback without additional hardware support. It was more useful for the electronic hydraulic servo actuator. Originality/value This was the research paper that analyzed the impact of the variable SFD gradience in the ASS servo system and presented an LPV control method to solve it. It was applicable for the SFD gradience changing in the linear and non-linear cases.

7

Chen, Jianchi, Dawei Gu, Ian Postlethwaite e Kannan Natesan. "Robust LPV Control of UAV with Parameter Dependent Performance". IFAC Proceedings Volumes 41, n. 2 (2008): 15070–75. http://dx.doi.org/10.3182/20080706-5-kr-1001.02550.

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8

Xie, W. "Robust control system design for polytopic stable LPV systems". IMA Journal of Mathematical Control and Information 20, n. 2 (1 giugno 2003): 201–16. http://dx.doi.org/10.1093/imamci/20.2.201.

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9

Maalej, Sonia, Alexandre Kruszewski e Lotfi Belkoura. "Robust Control for Continuous LPV System with Restricted-Model-Based Control". Circuits, Systems, and Signal Processing 36, n. 6 (20 settembre 2016): 2499–520. http://dx.doi.org/10.1007/s00034-016-0404-6.

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10

Cao, Guoyan, Karolos M. Grigoriadis e 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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Abstract (sommario):

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, appropriate frequency-dependent varying scaling parametric weighting functions are designed in the LPV control structure. The solution of a set of linear matrix inequalities (LMIs) leads to the LPV controller. A synchronous generator model is connected with the closed LPV control loop for examining the electrical subsystem performance obtained by an inner speed control loop. Simulation results of a 1.5 MW horizontal axis wind turbine model on the FAST platform illustrates the benefit of the LPV control and demonstrates the advantages of this proposed LPV controller, when compared with a traditional gain scheduling PI control and prior LPV control configurations. Enhanced structural load mitigation, improved power extraction, and good current performance were obtained from the proposed LPV control.

11

He, Xing, Wei Jiang e Caisheng Jiang. "Robust Controller Designing for an Air-Breathing Hypersonic Vehicle with an HOSVD-Based LPV Model". International Journal of Aerospace Engineering 2021 (3 dicembre 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 singular value decomposition (HOSVD). Third, the validity and applicability of the HOSVD-based LPV model are further demonstrated by designing a robust controller for command tracking control during maneuvering flight over a large envelope.

12

Chen, Fenghua, Xinguo Qiu, Khalid A. Alattas, Ardashir Mohammadzadeh e Ebrahim Ghaderpour. "A New Fuzzy Robust Control for Linear Parameter-Varying Systems". Mathematics 10, n. 18 (13 settembre 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 to speed up this operation. Lyapunov’s theory is used to guarantee the control system’s stability. Finally, to evaluate the performance of the proposed control system, the inverted pendulum has been investigated as a case study. The results show that the proposed method has good efficiency and performance.

13

Degtyarev, G. L., R. N. Faizutdinov e I. O. Spiridonov. "Multiobjective Robust Controller Synthesis for Nonlinear Mechanical System". Mekhatronika, Avtomatizatsiya, Upravlenie 19, n. 11 (8 novembre 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 actual system exhibits nonlinear behavior, nonlinearities are usually included in the uncertainty set of the plant. A disadvantage of this approach is that resulting controllers may be too conservative especially when nonlinearities are significant. The nonlinear H∞ optimal control theory developed on the basis of differential game theory is a natural extension of the linear robust control theory. Nonlinear theory methods ensure robust stability of designed control systems. However, to determine nonlinear H∞-control law, the partial differential equation have to be solved which is a rather complicated task. In addition, it is difficult to ensure robust performance of controlled processes when using this method. In this paper, methods of linear parameter-varying (LPV) systems are used to synthesize robust control law. It is shown, that Lagrange system may be adequately represented in the form of quasi-LPV model. From the computational point of view, the synthesis procedure is reduced to convex optimization techniques under constraints expressed in the form of linear matrix inequalities (LMIs). Measured parameters are incorporated in the control law, thus ensuring continuous adjustment of the controller parameters to the current plant dynamics and better performance of control processes in comparison with H∞-regulators. Furthermore, the use of the LMIs allows to take into account the transient performance requirements in the controller synthesis. Since the quasi-LPV system depends continuously on the parameter vector, the LMI system is infinite-dimensional. This infinitedimensional system is reduced to a finite set of LMIs by introducing a polytopic LPV representation. The example of multiobjective robust control synthesis for electro-optical device’s line of sight pointing and stabilization system suspended in two-axes inertially stabilized platform is given.

14

Dalila, Khamari, Makouf Abdessalem, Drid Said e Larbi Chrifi-Alaoui. "Robust linear parameter varying induction motor control with polytopic models". Serbian Journal of Electrical Engineering 10, n. 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 polytopic model because of speed and rotor resistance affine dependence their values can be estimated on line during systems operations. The simulation results are presented to confirm the effectiveness of the proposed approach where robustness stability and high performances have been achieved over the entire operating range of the induction motor.

15

Ku, Cheung-Chieh, e 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 corresponding sufficient conditions to solve the stabilization problems of this paper. In order to use convex optimization algorithm, the derived conditions are converted into Linear Matrix Inequality (LMI) form. Via solving those conditions, the gain-scheduled controller can be established such that the robust asymptotical stability andH∞performance of the disturbed uncertain stochastic system can be achieved in the sense of mean square. Finally, two numerical examples are applied to demonstrate the effectiveness and applicability of the proposed design method.

16

Jia, Qiusheng, Xinxing Shi, Yan Li e Huacong LI. "LPV Robust Controller Design with Regional Pole Assignment for an Aero-Engine". Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 37, n. 6 (dicembre 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 LPV output feedback controller with the closed-loop system pole placement in a given region, which satisfied robust H∞ performance requirement, is designed using the LMI method. Then the grid method is used to transform the Lyapunov functional which depend on the scheduling parameters into a single Lyapunov function, which can guarantee the system has good steady performance. Finally, simulation studies have carried out based on a certain turbofan engine. The simulation results show that the designed controller can realize the accurate tracking of control commands with response time less than 1.6 s, over shoot less than 1% and steady-state tracking error less than 0.1%. The control system can guarantee the global stability and has good robustness in the design envelope.

17

Najarzadeh, reza, maryam dehghani, mohammad hassan asemani e roozbeh abolpour. "Optimal Robust LPV Control Design for Novel Covid-19 Disease". Journal of Control 14, n. 5 (1 febbraio 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 e J. H. Park. "Robust model predictive control for LPV systems using relaxation matrices". IET Control Theory & Applications 1, n. 6 (1 novembre 2007): 1567–73. http://dx.doi.org/10.1049/iet-cta:20060525.

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19

Bendtsen, J. D., e K. Trangbaek. "Robust quasi-LPV control based on neural state-space models". IEEE Transactions on Neural Networks 13, n. 2 (marzo 2002): 355–68. http://dx.doi.org/10.1109/72.991421.

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20

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

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21

Németh, Balázs, Attila Lelkó e Péter Gáspár. "Robust LPV control synthesis for learning-aided driver assistance systems". IFAC-PapersOnLine 55, n. 35 (2022): 97–102. http://dx.doi.org/10.1016/j.ifacol.2022.11.296.

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22

Schaab, Konstantin, e Olaf Stursberg. "Robust Decentralized LPV Control for Transient Stability of Power Systems". IFAC-PapersOnLine 48, n. 30 (2015): 566–71. http://dx.doi.org/10.1016/j.ifacol.2015.12.440.

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23

Hadian, Mohsen, Amin Ramezani e Wenjun Zhang. "Robust Model Predictive Controller Using Recurrent Neural Networks for Input–Output Linear Parameter Varying Systems". Electronics 10, n. 13 (28 giugno 2021): 1557. http://dx.doi.org/10.3390/electronics10131557.

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Abstract (sommario):

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) is employed to solve real-time optimization problems with lower online computation. Regarding robustness, a new control law is developed, which comprises a fixed control gain (K) and a free perturbation (C). The proposed method enjoys a shrunken conservatism owing to the finding of a larger possible terminal region and using free control moves. The strategy is examined in an alkylation of benzene process and displays outstanding performance in both setpoint tracking and disturbance rejection problems. Moreover, the superiority of RNN over three conventional optimization algorithms is underlined in terms of MSE, the average time for solving the optimization problem, and the value of the cost function.

24

Hasseni, Seif-El-Islam, e 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, n. 4 (1 dicembre 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 of the weighting functions that represent the desired performance is solved by two approaches of evolutionary algorithms; Genetic Algorithms (GA) and Evolutionary Strategies (ES) to find the weighting functions’ optimal parameters. To validate the proposed approach, simulations are performed and they show the effectiveness of the proposed approach to obtain robust controllers against external signals, as well as the parametric uncertainties.

25

Su, Khac Huan, Kwankyun Byeon, Wonhee Kim e Youngwoo Lee. "LPV H∞ Control with an Augmented Nonlinear Observer for Sawyer Motors". Mathematics 10, n. 1 (21 dicembre 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 interpolation parameters in the LPV system on the tracking error performance. To be robust against disturbance, a state feedback controller with the LPV gain scheduling is determined by applying the H∞ control in the linear-matrix-inequality (LMI) technique. The closed-loop stability is proved through the Lyapunov theory. The effectiveness of the proposed control method is evaluated through simulation results and compared with the conventional proportional-integral-derivative (PID) control method to verify both the improved tracking error performance and a suitable disturbance rejection.

26

Li, Hongkun, Rui Huang, Yonghui Zhao e Haiyan Hu. "Maneuver load alleviation for high performance aircraft robust to flight condition variations". Journal of Vibration and Control 25, n. 5 (18 novembre 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 load alleviation, a controller based on recurrent neural networks is designed in the flight control. Finally, some numerical simulations are made to testify the performance and robustness of the MLA system.

27

Bianchi, Fernando D., e Ricardo S. Sánchez-Peña. "Robust identification/invalidation in an LPV framework". International Journal of Robust and Nonlinear Control 20, n. 3 (27 marzo 2009): 301–12. http://dx.doi.org/10.1002/rnc.1430.

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28

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

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29

GAO, Zhenxing, e Jun FU. "Robust LPV modeling and control of aircraft flying through wind disturbance". Chinese Journal of Aeronautics 32, n. 7 (luglio 2019): 1588–602. http://dx.doi.org/10.1016/j.cja.2019.03.029.

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30

Malik, Arshad Habib, Aftab Ahmed Memon e 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, n. 2 (1 aprile 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 parameters are dynamic in nature that makes the control problem more challenging. The Model is estimated experimentally by least square method using innovative plant operational data of opening positions of different valves as input variables and steam pressure as an output variable and cold leg coolant temperature coefficient of reactivity, hot leg coolant temperature coefficient, steam flow rate and turbine power as dynamic scheduling parameters. A switching controller is designed to address variable conditions of steam pressure for the actuation of dump valves, relief valves and safety valves in SDS. A robust fractional order LPV switching H∞ (RFO-LPV-SWH∞) controllers are formulated and designed for FO-MSP-MISO-LPV model. The design of RFO-LPV-SWH∞ controllers is another significant contribution in switching mode with non-integer and LPV hybrid framework. RFO-LPV-SWH∞ controllers are tested, simulated and validated against benchmark transients as laid down in Final Safety Analysis Report (FSAR) of PWR-type NPP. The input and output variables at first and second vertex of polytope are fast reference tracking under highly nonlinear uncertain dynamics of SDS. Closed loop simulation experiments are conducted and proved that the proposed closed framework is robust in performance under parametric uncertainty.

31

Mystkowski, Arkadiusz. "Robust Optimal Control of MAV Based on Linear-Time Varying Decoupled Model Dynamics". Solid State Phenomena 198 (marzo 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.

32

Patton, Ron, Lejun Chen e Supat Klinkhieo. "An LPV pole-placement approach to friction compensation as an FTC problem". International Journal of Applied Mathematics and Computer Science 22, n. 1 (1 marzo 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 suitable LMI regions, guaranteeing both stability and performance of a multi-fault LPV estimator employed within an FTC structure. The proposed design strategy is illustrated using a nonlinear two-link manipulator system with friction forces acting simultaneously at each joint. The friction forces, regarded as a special case of actuator faults, are estimated and their effect is compensated within a polytope controller system, yielding a robust form of active FTC that is easy to apply to real robot systems.

33

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

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Abstract (sommario):

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 performance.

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Yang, Xing, Lu Xiong, Bo Leng, Dequan Zeng e Guirong Zhuo. "Design, Validation and Comparison of Path Following Controllers for Autonomous Vehicles". Sensors 20, n. 21 (24 ottobre 2020): 6052. http://dx.doi.org/10.3390/s20216052.

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Abstract (sommario):

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 optimization problem is solved by CVXGEN. The nonlinear active disturbance rejection control (ADRC) method is applied to the second lateral controller that is easy to be implemented and robust to parametric uncertainties and disturbances, and the pure pursuit algorithm serves as a benchmark. Simulation results in different scenarios demonstrate the effectiveness of the proposed control schemes, and a comparison is made to highlight the advantages and drawbacks. It can be concluded that the LPV-MPC has some trouble to handle uncertainties while the nonlinear ADRC performs slight worse tracking but has strong robustness. With the parallel development of the control theory and computing power, robust MPC may be the future direction.

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Ríos, Héctor, Susana Viridiana Gutiérrez Martínez, Tarek Raïssi e Denis Efimov. "An Integral Sliding–Mode–based Interval Predictive Control for Constrained LPV Systems". Memorias del Congreso Nacional de Control Automático 6, n. 1 (27 ottobre 2023): 103–8. http://dx.doi.org/10.58571/cnca.amca.2023.011.

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Abstract (sommario):

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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Jafar, Adnan, Aamer Iqbal Bhatti, Sarvat M. Ahmad e 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, n. 7 (8 agosto 2018): 1833–48. http://dx.doi.org/10.1177/0142331218788121.

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Abstract (sommario):

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 solve the control optimization problem in the proposed theorem using the linear matrix inequality (LMI) approach. It is shown that the proposed theorem is suitable for the multivariable control of multiple input multiple output (MIMO) coupled non-linear systems. In particular, in presence of cross coupled dynamics, external disturbances, changing operating conditions and time varying parameters. The effectiveness of the proposed technique is demonstrated in simulation as well as validated with experiments.

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

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Abstract (sommario):

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

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Abstract (sommario):

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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Wen, Nuan, Zhenghua Liu, Yang Sun e 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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Abstract (sommario):

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-invariant (LTI) systems. The sufficient condition in form of linear matrix inequality (LMI) constraints is derived for the existence of a reduced-order sliding mode, in which the dynamics can be ensured to keep robust stability and L2 gain performance. The tensor-product (TP) model transformation approach can be directly applied to solve infinite LMIs belonging to the polynomial parameter-dependent LPV system. Then, by the parameter-dependent Lyapunov function stability analysis, the synthesized FSMC is proved to drive the LPV system trajectories toward the predefined switching surface with a finite time arrival. Comparative simulation results in the nonlinear model demonstrate the robustness and effectiveness of this approach.

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Song, Lei, e Jianying Yang. "Robust reliable tracking controller design against actuator faults for LPV systems". Asian Journal of Control 13, n. 6 (2 dicembre 2010): 1075–81. http://dx.doi.org/10.1002/asjc.286.

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Saeed, Azmat, Aamer I. Bhatti e Fahad M. Malik. "LMIs-Based LPV Control of Quadrotor with Time-Varying Payload". Applied Sciences 13, n. 11 (28 maggio 2023): 6553. http://dx.doi.org/10.3390/app13116553.

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Abstract (sommario):

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 mass, time-varying inertia, mass flow rate, and large tilt angles. The control strategy is designed by solving LMIs derived from quadratic H∞ performance and D-stability. The robust stability and quadratic H∞ performance are assessed by LMIs. The efficacy of the proposed methodology is established using numerical simulations, and its performance is compared to the linear time-invariant (LTI) H∞ design with pole placement constraints. The results obtained show that the LPV control scheme gives better tracking performance in the presence of time-varying parameters, noise, and external disturbances without actuator saturation. In comparison to the LTI design technique, the proposed LPV scheme improves the rise time (tr), settling time (ts), and mean squared error (MSE) by up to 14%, 15%, and 30%, respectively. Moreover, smooth transitions are observed in the tilt angles and control signals with the LPV scheme, contrary to the LTI controller, which exhibits significant oscillations.

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Rotondo, Damiano, Fatiha Nejjari e Vicenç Puig. "Robust state-feedback control of uncertain LPV systems: An LMI-based approach". Journal of the Franklin Institute 351, n. 5 (maggio 2014): 2781–803. http://dx.doi.org/10.1016/j.jfranklin.2014.01.018.

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

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Hooshmandi, Kaveh, Farhad Bayat, Mohammad Reza Jahed-Motlagh e Ali Akbar Jalali. "Polynomial LPV approach to robust H ∞ control of nonlinear sampled-data systems". International Journal of Control 93, n. 9 (19 novembre 2018): 2145–60. http://dx.doi.org/10.1080/00207179.2018.1547422.

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Buzachero, Luiz F. S., Edvaldo Assunção, Marcelo C. M. Teixeira e Emerson R. P. da Silva. "Switched Optimized Robust Control of Uncertain LPV Systems Subject to Structural Faults". IFAC-PapersOnLine 51, n. 25 (2018): 353–58. http://dx.doi.org/10.1016/j.ifacol.2018.11.132.

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Theißen, Moritz, Konstantin Schaab e Olaf Stursberg. "Voltage Stability of Power Grids with PV Plants using Robust LPV-Control". IFAC-PapersOnLine 49, n. 27 (2016): 54–59. http://dx.doi.org/10.1016/j.ifacol.2016.10.719.

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Schaab, Konstantin, e Olaf Stursberg. "Decentralized Robust Control of Power Grids Using LPV-Models of DAE-Systems". IFAC-PapersOnLine 48, n. 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, n. 7 (2023): 133–52. http://dx.doi.org/10.12700/aph.20.7.2023.7.8.

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Varrier, Sébastien, Damien Koenig e John J. Martinez. "Robust fault detection for Uncertain Unknown Inputs LPV system". Control Engineering Practice 22 (gennaio 2014): 125–34. http://dx.doi.org/10.1016/j.conengprac.2013.10.002.

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Varga, Andreas, e Daniel Ossmann. "LPV model-based robust diagnosis of flight actuator faults". Control Engineering Practice 31 (ottobre 2014): 135–47. http://dx.doi.org/10.1016/j.conengprac.2013.11.004.

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