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Автор: Grafiati

Опубліковано: 24 січня 2023

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1

Haddad, Wassim M., Vijaysekhar Chellaboina, Jerry L. Fausz, and Alexander Leonessa. "Optimal non-linear robust control for non-linear uncertain systems." International Journal of Control 73, no. 4 (January 2000): 329–42. http://dx.doi.org/10.1080/002071700219687.

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2

Liang, Yew-Wen, and Der-Cherng Liaw. "Robust control of non-linear affine systems." Applied Mathematics and Computation 137, no. 2-3 (May 2003): 337–47. http://dx.doi.org/10.1016/s0096-3003(02)00129-7.

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3

Al-Khazraji, Ayman, and Karim M. Aljebory. "Robust Adaptive Type-2 Fuzzy Sliding Mode Control for Non-Linear uncertain SISO systems." Journal of Control Engineering and Technology 4, no. 4 (October 31, 2014): 243–56. http://dx.doi.org/10.14511/jcet.2014.040401.

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4

Spurgeon, S. K. "Non-Linear Control for Uncertain Systems." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 208, no. 4 (November 1994): 205–13. http://dx.doi.org/10.1243/pime_proc_1994_208_333_02.

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Анотація:

This paper presents a review of a number of state-of-the-art non-linear control design techniques which may be readily applied to solve practical problems in a robust fashion. It is first shown that non-linear controllers may be designed using straightforward linear models with minimal recourse to abstract mathematical concepts. More involved philosophies for robust control system design of inherently non-linear plants are then briefly described. A straightforward yet rigorous design framework is then presented to implement the philosophy. Tutorial examples are presented throughout the paper in order to illustrate major points of interest.

5

Liu, Yusheng. "Robust adaptive control of uncertain non-linear systems with non-linear parameterisation." International Journal of Modelling, Identification and Control 1, no. 2 (2006): 151. http://dx.doi.org/10.1504/ijmic.2006.010091.

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6

Shergei, M., U. Shaked та C. E. De Souza. "Robust ℋ∞ non-linear estimation". International Journal of Adaptive Control and Signal Processing 10, № 4-5 (липень 1996): 395–408. http://dx.doi.org/10.1002/(sici)1099-1115(199607)10:4/5<395::aid-acs370>3.0.co;2-n.

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7

Yamamoto, Ikuo. "Robust and non-linear control of marine system." International Journal of Robust and Nonlinear Control 11, no. 13 (2001): 1285–341. http://dx.doi.org/10.1002/rnc.606.

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8

Hammer, Jacob. "Robust stabilization of non-linear systems." International Journal of Control 49, no. 2 (February 1989): 629–53. http://dx.doi.org/10.1080/00207178908559657.

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9

Kelemen, Matei, Ouassima Akhrif, and Azeddine Kaddouri. "Linear robust control of a synchronous motor, experimental comparison with non-linear control." International Journal of Control 73, no. 7 (January 2000): 624–38. http://dx.doi.org/10.1080/002071700219461.

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10

Amiri-M, Amir-A., M. R. Gharib, M. Moavenian, and K. Torabiz. "Modelling and control of a SCARA robot using quantitative feedback theory." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 223, no. 7 (August 3, 2009): 919–28. http://dx.doi.org/10.1243/09596518jsce733.

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In this paper, a practical method to design a robust controller for a SCARA robot using quantitative feedback theory (QFT) is proposed. The models used to describe robots contain uncertainties that are the result of insufficient knowledge on the dynamics of the robot, external disturbances, pay load changes, and friction, etc. Thus, the application of robust control methods to create the precise control of robots is of considerable interest. This paper considers a robot arm manipulator, a system whose models contain non-linear coupled transfer functions. In the first step of applying the QFT technique the non-linear plant is converted into a family of linear uncertain plants. This is achieved using a fixed-point theorem and then suitable disturbance rejection bounds are found. A robust controller is designed for the tracking problem. Non-linear simulations on the tracking problem for a three-dimension elliptical path are performed and the results highlight the success of the designed controllers and pre-filters. The presented results indicate that applying the proposed technique successfully overcomes the obstacles to robust control of non-linear SCARA robots.

11

Gallegos, Javier A., and Manuel A. Duarte-Mermoud. "Robust mixed order backstepping control of non-linear systems." IET Control Theory & Applications 12, no. 9 (June 12, 2018): 1276–85. http://dx.doi.org/10.1049/iet-cta.2017.0905.

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12

Magni, L. "On robust tracking with non-linear model predictive control." International Journal of Control 75, no. 6 (January 2002): 399–407. http://dx.doi.org/10.1080/00207170110115626.

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13

Fulwani, D., B. Bandyopadhyay, and L. Fridman. "Non-linear sliding surface: towards high performance robust control." IET Control Theory & Applications 6, no. 2 (2012): 235. http://dx.doi.org/10.1049/iet-cta.2010.0727.

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14

Vesely, V., J. Simovec, and D. P. Papadopoulos. "A Robust Non-Linear Control Design for a Turbogenerator." IFAC Proceedings Volumes 30, no. 21 (September 1997): 275–80. http://dx.doi.org/10.1016/s1474-6670(17)41451-0.

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15

JOHANSEN, TOR A., and PETROS A. IOANNOU. "ROBUST ADAPTIVE CONTROL OF MINIMUM PHASE NON-LINEAR SYSTEMS." International Journal of Adaptive Control and Signal Processing 10, no. 1 (January 1996): 61–78. http://dx.doi.org/10.1002/(sici)1099-1115(199601)10:1<61::aid-acs387>3.0.co;2-h.

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16

Herrero, J. M., X. Blasco, M. Martínez, C. Ramos, and J. Sanchis. "Non-linear robust identification using evolutionary algorithms." Engineering Applications of Artificial Intelligence 21, no. 8 (December 2008): 1397–408. http://dx.doi.org/10.1016/j.engappai.2008.05.001.

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17

Binazadeh, T., and M.-J. Yazdanpanah. "Robust partial control design for non-linear control systems: a guidance application." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 226, no. 2 (September 16, 2011): 233–42. http://dx.doi.org/10.1177/0959651811413013.

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In this paper, a general approach for robust partial stabilization of uncertain non-linear systems is presented. In this approach, the non-linear dynamic system is divided into two subsystems, called the first and the second subsystems. This division is done based on the required stability properties of the system’s states. The reduced input vector (the vector that includes components of the input vector appearing in the first subsystem) is designed to asymptotically stabilize the first subsystem. The proposed scheme is then applied for designing a guidance law as a potential application. Indeed, the paper presents a new approach to the missile guidance problem and shows that asymptotic stability behaviour is not realistic for all states of the guidance system. The effectiveness of the proposed guidance law in interception of manoeuvring targets is demonstrated analytically and through computer simulations.

18

Marconi, L., and R. Naldi. "NON LINEAR ROBUST CONTROL OF AN HELICOPTER FOR TRAJECTORY TRACKING." IFAC Proceedings Volumes 39, no. 15 (2006): 536–41. http://dx.doi.org/10.3182/20060906-3-it-2910.00090.

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19

Feng, W., and I. Postlethwaite. "Robust Non-Linear H∞/Adaptive Control of Robot Manipulator Motion." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 208, no. 4 (November 1994): 221–30. http://dx.doi.org/10.1243/pime_proc_1994_208_335_02.

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In robotics, despite considerable effort to minimize system modelling errors, uncertainties are always present and sometimes significant. In this paper, modelling errors are first represented by a class of bounded disturbances in the input channels (torques) of the robot. A measure of the robot system's ability to reject these disturbances is formulated in an L2 gain sense and a control design is subsequently proposed to achieve optimal disturbance rejection. If more detailed information is available on the plant-model mismatch, then the control design can be modified to incorporate an adaptive scheme (with explicit parameter updating laws) in order to reduce the conservativeness of the original design and to improve robust performance of the overall system.

20

Nguang, Sing Kiong. "Robust global L2-gain control of structural non-linear systems." International Journal of Control 72, no. 11 (January 1999): 1033–42. http://dx.doi.org/10.1080/002071799220588.

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21

Sakthivel, R., and H. Ito. "Non-linear robust boundary control of the Kuramoto-Sivashinsky equation." IMA Journal of Mathematical Control and Information 24, no. 1 (March 23, 2006): 47–55. http://dx.doi.org/10.1093/imamci/dnl009.

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22

El-Farra, Nael H., and Panagiotis D. Christofides. "Robust near-optimal output feedback control of non-linear systems." International Journal of Control 74, no. 2 (January 2001): 133–57. http://dx.doi.org/10.1080/00207170150203480.

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23

Guo, L., and M. Malabre. "Robust H ∞ control for descriptor systems with non-linear uncertainties." International Journal of Control 76, no. 12 (January 2003): 1254–62. http://dx.doi.org/10.1080/0020717031000147494.

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24

Shumsky, Alexey Ye. "Robust Failure Detection and Isolation in Non-Linear Control Systems." IFAC Proceedings Volumes 25, no. 20 (September 1992): 159–64. http://dx.doi.org/10.1016/s1474-6670(17)49855-7.

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25

Yang, Zi Jiang, Youichirou Fukushima, Shunshoku Kanae, and Kiyoshi Wada. "Decentralised robust control of interconnected uncertain non-linear mechanical systems." International Journal of Intelligent Systems Technologies and Applications 8, no. 1/2/3/4 (2010): 114. http://dx.doi.org/10.1504/ijista.2010.030194.

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26

HAMADA, KAZUYASU, and MASAYUKI SUZUKI. "Robust adaptive algorithm with non-linear decay term." International Journal of Control 47, no. 3 (March 1988): 665–80. http://dx.doi.org/10.1080/00207178808906045.

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27

Zuo, Zhiqiang, Jinzhi Wang, and Lin Huang. "Robust stabilization for non-linear discrete-time systems." International Journal of Control 77, no. 4 (March 10, 2004): 384–88. http://dx.doi.org/10.1080/00207170410001663543.

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28

Petridis, A. P., and A. T. Shenton. "Linear Robust Control of Identified State-Space Non-Linear Inverse Compensated SI Engine." Inverse Problems in Engineering 10, no. 3 (January 2002): 255–70. http://dx.doi.org/10.1080/10682760290024445.

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29

Deng, M., A. Inoue, and S. Bi. "Robust non-linear control and tracking design for multi-input multi-output non-linear perturbed plants." IET Control Theory & Applications 3, no. 9 (September 1, 2009): 1237–48. http://dx.doi.org/10.1049/iet-cta.2008.0218.

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30

Fang, Y. "New robust stability results for linear systems with structured non-linear perturbations." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 212, no. 4 (June 1, 1998): 241–47. http://dx.doi.org/10.1243/0959651981539433.

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The robust stability of linear systems with unstructured, structured or non-linear perturbations is investigated in a unifying framework. New sufficient conditions in terms of matrix Riccati inequalities are obtained. Some previously known results are generalized.

31

., Senthilkumar K. "COMPARATIVE ANALYSIS OF ROBUST CONTROL AND CONVENTIONAL CONTROL FOR A NON-LINEAR PROCESS." International Journal of Research in Engineering and Technology 07, no. 07 (July 25, 2018): 137–40. http://dx.doi.org/10.15623/ijret.2018.0707017.

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32

Zhu, Rusong, Guofu Yin, Gengsheng Tang, Hai Wang, and Shuangxi Zhang. "Temperature trajectory control of cryogenic wind tunnel with robust L1 adaptive control." Transactions of the Institute of Measurement and Control 40, no. 13 (October 9, 2017): 3675–89. http://dx.doi.org/10.1177/0142331217728569.

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Temperature control in a cryogenic wind tunnel is the key to realizing finely controlled Reynolds number close to true flight. This study deploys the L1 adaptive control methodology to ensure the total temperature profile of the cryogenic wind tunnel tracks a specified reference trajectory. After introducing a non-linear model of a cryogenic wind tunnel and a linear temperature model, a linear–quadratic–Gaussian (LQG) controller is implemented as the baseline controller. The L1 adaptive controller with piecewise constant adaptive law is used as an augmentation to the baseline controller to cancel the matched and unmatched uncertainties within the actuator’s bandwidth. By introducing two modifications to the standard L1 adaptive controller, which are the transportation delay modelling in the state predictor and the non-linear state dependent filter, the L1 adaptive controller improves the performance of the baseline controller in the presence of uncertainties in temperature control, guaranteeing proper stability and delay margin. The simulation results and analysis demonstrate the effectiveness of the proposed control architecture. The main contribution of this paper lies in the first applications of L1 adaptive control to the wind tunnel control problem and the non-linear state dependent filter in L1 adaptive control structure.

33

CHIANG, CHIANG-CHENG, and BOR-SEN CHEN. "Robust stabilization against non-linear time-varying uncertainties." International Journal of Systems Science 19, no. 5 (January 1988): 747–60. http://dx.doi.org/10.1080/00207728808967640.

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34

CHEN, Y. H. "Adaptive robust observers for non-linear uncertain systems." International Journal of Systems Science 21, no. 5 (May 1990): 803–14. http://dx.doi.org/10.1080/00207729008910416.

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35

Quintas, M. R., E. Richard, and S. Scavarda. "Implicit Non-Linear Robust Control for an Electrohydraulic System with Uncertainties." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 210, no. 2 (May 1996): 103–11. http://dx.doi.org/10.1243/pime_proc_1996_210_443_02.

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This paper deals with tracking the position of a linear cylinder moving a mass and controlled by a servovalve. The model of this system is non-linear with respect to state and input and has bounded uncertainties. Uncertainties are considered about the leakage flowrate of the servovalve and about the mass in movement. An implicit non-linear control with a robust term designed by the Corless-Leitmann approach is described step by step. Simulation results are shown in order to point out the advantages of this approach.

36

El-ghatwary, Magdy G., and Steven X. Ding. "Robust Fuzzy Fault Detection for Non-Linear Stochastic Dynamic Systems." Open Automation and Control Systems Journal 2, no. 1 (January 1, 2009): 45–53. http://dx.doi.org/10.2174/1874444300902010045.

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37

El-ghatwary, Magdy G., and Steven X. Ding. "Robust Fuzzy Fault Detection for Non-Linear Stochastic Dynamic Systems." Open Automation and Control Systems Journal 2, no. 2 (August 19, 2009): 45–53. http://dx.doi.org/10.2174/1874444300902020045.

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38

Shokrollahi, Ali, and Saeed Shamaghdari. "Robust H∞ model predictive control for constrained Lipschitz non-linear systems." Journal of Process Control 104 (August 2021): 101–11. http://dx.doi.org/10.1016/j.jprocont.2021.06.007.

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39

Wang, J. P., H. S. Cho, and B. G. Cao. "A servo-controller design based on non-linear adaptive robust control." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 221, no. 7 (July 1, 2007): 1147–51. http://dx.doi.org/10.1243/09544054jem550.

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Based on a non-linear model of a computer numerical control (CNC) system, a general adaptive robust controller (ARC) is presented in this paper. The ARC was used to treat problems including the compensation of friction non-linearity, parameter variation, and unmodelled dynamics in the design of a CNC system. It can enhance stability robustness and performance robustness. The simulation results show the effectiveness of the method.

40

Tang, Dejun, Dongqing Zhang, Yonghu Yang, and Zhenyu Liu. "Robust non-fragile control for the switched discrete-time linear system." International Journal of Modelling, Identification and Control 10, no. 1/2 (2010): 152. http://dx.doi.org/10.1504/ijmic.2010.033859.

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41

Kim, Hag Seong, Kyo-Il Lee, and Young Man Cho. "Robust two-stage non-linear control of a hydraulic servo-system." International Journal of Control 75, no. 7 (January 2002): 502–16. http://dx.doi.org/10.1080/00207170110112845.

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42

Mohammad-Hoseini, S., M. Farrokhi, and A. J. Koshkouei. "Robust adaptive control of uncertain non-linear systems using neural networks." International Journal of Control 81, no. 8 (August 2008): 1319–30. http://dx.doi.org/10.1080/00207170701771885.

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43

Yao, Bin, and Masayoshi Tomizuka. "Adaptive Robust Control of Non linear Systems: Effective Use of Information." IFAC Proceedings Volumes 30, no. 11 (July 1997): 873–78. http://dx.doi.org/10.1016/s1474-6670(17)42956-9.

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44

KHORASANI, K. "Robust stabilization of non-linear systems with unmodelled dynamics." International Journal of Control 50, no. 3 (September 1989): 827–44. http://dx.doi.org/10.1080/00207178908953400.

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45

Chen, Yudong, Zhengxin Weng, and Songjiao Shi. "Robust fault diagnosis for non-linear difference-algebraic systems." International Journal of Control 76, no. 15 (January 2003): 1560–69. http://dx.doi.org/10.1080/00207170310001605034.

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46

Xu, Ze Yin. "Non-Fragile Robust H∞ Control for Linear Uncertain Switched Systems with Delayed Perturbations." Advanced Materials Research 562-564 (August 2012): 1968–71. http://dx.doi.org/10.4028/www.scientific.net/amr.562-564.1968.

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The non-fragile robust H∞ controller was designed for a class of uncertain switched systems with delayed perturbations under additive perturbations of controller gain. A sufficient condition for the solvability of the non-fragile robust H∞ controller via state feedback was proved and presented, which based on a proper Lyapunov function and switching strategy, non-fragile robust H∞ controller can be obtained only by solving linear matrix inequalities. The systems under actions of the given controller are not only robust but also satisfy H∞ performance when controller changes, and thus have better adaptability against variety of the environment parameters. The simulation results show the effectiveness of the design method.

47

Xiong, K., L. Liu, and Y. Liu. "Non-linear robust filter design for satellite attitude determination." IET Control Theory & Applications 4, no. 7 (July 1, 2010): 1222–34. http://dx.doi.org/10.1049/iet-cta.2009.0076.

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48

IHEDRANE, Yasmine, Chakib El Bekkali, Madiha El Ghamrasni, Sara Mensou, and Badre Bossoufi. "Improved wind system using non-linear power control." Indonesian Journal of Electrical Engineering and Computer Science 14, no. 3 (June 1, 2019): 1148. http://dx.doi.org/10.11591/ijeecs.v14.i3.pp1148-1158.

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Анотація:

<p>This article, present a new contribution to the control of wind energy systems, a robust nonlinear control of active and reactive power with the use of the Backstepping and Sliding Mode Control approach based on a doubly fed Induction Generator power (DFIG-Generator) in order to reduce the response time of the wind system. In the first step, a control strategy of the MPPT for the extraction of the maximum power of the turbine generator is presented. Subsequently, the Backstepping control technique followed by the sliding mode applied to the wind systems will be presented. These two types of control system rely on the stability of the system using the LYAPUNOV technique. Simulation results show performance in terms of set point tracking, stability and robustness versus wind speed variation. </p>

49

Feng, Chieh Chuan, Li Peng Yin, and En Chih Chang. "Robust Control Design Based-On Integral Sliding-Mode Control." Applied Mechanics and Materials 284-287 (January 2013): 2301–4. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.2301.

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This paper proposes a robust control design based-on integral sliding-mode and H2–norm performance criterion to handle a class of time-varying systems with perturbations including non-linearities and disturbances. The stabilization problems for such systems are studied: integral slid-ing-mode is designated to completely nullify the matched perturbations and, in the meantime, elim-inate the reaching phase to the sliding surface, while H2–norm is a robust linear control measured for system on the sliding surface. In addition to the integral sliding mode control, the contribution of the paper is to implement a parameter-dependent Lyapunov function for H2–norm robust linear control that the overall designed system is less conservative for the system with both matched and unmatched perturbations.

50

Bamani, Ali H., and Ahmed I. Iskanderani. "Robust approximate non-interacting control design for a class of non-linear stochastic systems." Optimal Control Applications and Methods 10, no. 3 (July 1989): 275–83. http://dx.doi.org/10.1002/oca.4660100306.

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