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Journal articles on the topic 'Robust control strategies'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Trottemant, E. J., C. W. Scherer, M. Weiss, and A. Vermeulen. "Robust Missile Feedback Control Strategies." Journal of Guidance, Control, and Dynamics 33, no. 6 (2010): 1837–46. http://dx.doi.org/10.2514/1.48844.

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2

Murarami, T., and K. Ohnishi. "Robust and Adaptive Control Strategies." IFAC Proceedings Volumes 25, no. 29 (1992): 367–72. http://dx.doi.org/10.1016/s1474-6670(17)50594-7.

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3

Gil-Martínez, M., and M. García-Sanz. "ROBUST SPECIFICATION INFLUENCE ON FEEDBACK CONTROL STRATEGIES." IFAC Proceedings Volumes 35, no. 1 (2002): 425–30. http://dx.doi.org/10.3182/20020721-6-es-1901.00404.

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4

Zhu, Kaicheng, and Hai Bao. "Research on Robust Control Strategies for VSC-HVDC." IOP Conference Series: Earth and Environmental Science 108 (January 2018): 052077. http://dx.doi.org/10.1088/1755-1315/108/5/052077.

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5

Stîngă, Florin, Marius Marian, and Dan Selișteanu. "Robust Estimation-Based Control Strategies for Induction Motors." Complexity 2020 (July 29, 2020): 1–14. http://dx.doi.org/10.1155/2020/9235701.

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This work proposes a realistic solution to the control problem of sensorless induction motors. Due to some important aspects related to their construction and reliability, the induction motors are extensively used in many modern industrial applications. Considering that the system is facing the lack of hardware sensors, the proposed complex control strategies are based on the estimation of unavailable system variables and parameters. In order to control the rotor speed, two robust control strategies are proposed: a modified super-twisting adaptive technique and a model predictive technique. Th

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6

Pinto, Jefferson Wellano Oliveira, Juan Alberto Rojas Tueros, Bernardo Horowitz, Silvana Maria Bastos Afonso da Silva, Ramiro Brito Willmersdorf, and Diego Felipe Barbosa de Oliveira. "Gradient-free strategies to robust well control optimization." Computational Geosciences 24, no. 6 (2019): 1959–78. http://dx.doi.org/10.1007/s10596-019-09888-7.

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7

Bakker, Craig, Arnab Bhattacharya, Samrat Chatterjee, and Draguna L. Vrabie. "Metagames and Hypergames for Deception-Robust Control." ACM Transactions on Cyber-Physical Systems 5, no. 3 (2021): 1–25. http://dx.doi.org/10.1145/3439430.

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Increasing connectivity to the Internet for remote monitoring and control has made cyber-physical systems more vulnerable to deliberate attacks; purely cyber attacks can thereby have physical consequences. Long-term, stealthy attacks such as Stuxnet can be described as Advanced Persistent Threats (APTs). Here, we extend our previous work on hypergames and APTs to develop hypergame-based defender strategies that are robust to deception and do not rely on attack detection. These strategies provide provable bounds—and provably optimal bounds—on the attacker payoff. Strategies based on Bayesian pr

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8

Ottoni, Amanda G. S., Ricardo H. C. Takahashi, and Guilherme V. Raffo. "Stability Constraints for Robust Model Predictive Control." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/870189.

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This paper proposes an approach for the robust stabilization of systems controlled by MPC strategies. Uncertain SISO linear systems with box-bounded parametric uncertainties are considered. The proposed approach delivers some constraints on the control inputs which impose sufficient conditions for the convergence of the system output. These stability constraints can be included in the set of constraints dealt with by existing MPC design strategies, in this way leading to the “robustification” of the MPC.

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9

Adlane, Benlatreche, Knittel Dominique, and Ostertag Eric. "Robust Decentralized Control Strategies for Large Scale Web Handling Systems." IFAC Proceedings Volumes 37, no. 11 (2004): 585–90. http://dx.doi.org/10.1016/s1474-6670(17)31672-5.

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10

Zaidi, Imen, Mohamed Chtourou, and Mohamed Djemel. "Robust Neural Control Strategies for Discrete-Time Uncertain Nonlinear Systems." International Journal of Computer Applications 143, no. 10 (2016): 23–30. http://dx.doi.org/10.5120/ijca2016910377.

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11

Benlatreche, Adlane, Dominique Knittel, and Eric Ostertag. "Robust decentralised control strategies for large-scale web handling systems." Control Engineering Practice 16, no. 6 (2008): 736–50. http://dx.doi.org/10.1016/j.conengprac.2006.03.003.

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12

Petre, Emil, Dan Selişteanu, and Monica Roman. "Nonlinear robust adaptive control strategies for a lactic fermentation process." Journal of Chemical Technology & Biotechnology 93, no. 2 (2017): 518–26. http://dx.doi.org/10.1002/jctb.5383.

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13

Glizer, V. Y., and V. Turetsky. "Robust Transferable Sets of Linear Transferring Strategies." Journal of Optimization Theory and Applications 145, no. 1 (2009): 36–52. http://dx.doi.org/10.1007/s10957-009-9618-0.

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14

Rossiter, J. A., B. Kouvaritakis, and M. J. Rice. "A numerically robust state-space approach to stable-predictive control strategies." Automatica 34, no. 1 (1998): 65–73. http://dx.doi.org/10.1016/s0005-1098(97)00171-4.

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15

Lee, Seon-Woo, and Jong-Hwan Kim. "Friction Identification Using Evolution Strategies and Robust Control of Positioning Tables." Journal of Dynamic Systems, Measurement, and Control 121, no. 4 (1999): 619–24. http://dx.doi.org/10.1115/1.2802525.

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This paper presents an identification technique using evolution strategies (ES) for an integrated friction model of a positioning table. The friction model is based on Karnopp’s friction-velocity model with the rising static friction and spring-like property. Using the (μ + λ)-ES, the system parameters are identified with the experimental input and output data. The proposed control law consists of a conventional linear feedback control input, a friction compensation term and a sliding control input. The proposed control scheme can guarantee the stability of the overall system, even in the pres

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16

Bauso, Dario, Franco Blanchini, and Raffaele Pesenti. "ROBUST CONTROL STRATEGIES FOR MULTI—INVENTORY SYSTEMS WITH AVERAGE FLOW CONSTRAINTS." IFAC Proceedings Volumes 39, no. 5 (2006): 77–82. http://dx.doi.org/10.3182/20060607-3-it-3902.00017.

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17

Mahmoud, M. S. "Design of control strategies for robust dynamic routing in traffic networks." IET Control Theory & Applications 5, no. 15 (2011): 1716–28. http://dx.doi.org/10.1049/iet-cta.2010.0578.

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18

Casavola, A., D. Famularo, and G. Franzè. "Norm-bounded robust MPC strategies for constrained control of nonlinear systems." IEE Proceedings - Control Theory and Applications 152, no. 3 (2005): 285–95. http://dx.doi.org/10.1049/ip-cta:20041307.

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19

Singh, Bhim, Rohini Sharma, and Seema Kewat. "Robust Control Strategies for SyRG-PV and Wind-Based Islanded Microgrid." IEEE Transactions on Industrial Electronics 68, no. 4 (2021): 3137–47. http://dx.doi.org/10.1109/tie.2020.2978723.

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20

Yin, Hang, Xu Zhang, Xianlin Huang, and Hongqian Lu. "Two novel robust tracking control strategies for eliminating aircraft wing rock." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 8 (2018): 3042–55. http://dx.doi.org/10.1177/0954410018794807.

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Nonlinearities are essential features in the model of aircraft wing rock system and limit cycle is a typical phenomenon when flying without any control force. In this work, we concentrate on two robust tracking control schemes for automatic flight control systems by using forwarding technique. Combining forwarding technique with adaptive control and disturbance observer, manifolds are represented as insensitivity to parameter uncertainties and external disturbances. A second-order filter is employed to compute mappings and their analytic derivatives at each step of the design. The global, unif

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21

Bauso, Dario, Franco Blanchini, and Raffaele Pesenti. "Robust control strategies for multi–inventory systems with average flow constraints." Automatica 42, no. 8 (2006): 1255–66. http://dx.doi.org/10.1016/j.automatica.2005.12.006.

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22

Mhalla, Anis, Nabil Jerbi, Simon Collart Dutilleul, Etienne Craye, and Mohamed Benrejeb. "Robust control strategies facing disturbances in manufacturing workshops with time constraints." Computers & Industrial Engineering 65, no. 2 (2013): 268–76. http://dx.doi.org/10.1016/j.cie.2013.03.003.

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23

Petre, Emil, Dan Selişteanu, and Dorin Şendrescu. "Adaptive and robust-adaptive control strategies for anaerobic wastewater treatment bioprocesses." Chemical Engineering Journal 217 (February 2013): 363–78. http://dx.doi.org/10.1016/j.cej.2012.11.129.

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24

Branger, Nicole, and Antje Mahayni. "Tractable hedging: An implementation of robust hedging strategies." Journal of Economic Dynamics and Control 30, no. 11 (2006): 1937–62. http://dx.doi.org/10.1016/j.jedc.2005.06.014.

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25

Verran, Joanna, Sarah Jackson, Antony Scimone, Peter Kelly, and James Redfern. "Biofilm Control Strategies: Engaging with the Public." Antibiotics 9, no. 8 (2020): 465. http://dx.doi.org/10.3390/antibiotics9080465.

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There are few peer-reviewed publications about public engagement with science that are written by microbiologists; those that exist tend to be a narrative of an event rather than a hypothesis-driven investigation. However, it is relatively easy for experienced scientists to use a scientific method in their approach to public engagement. This short communication describes three public engagement activities hosted by the authors, focused on biofilm control: hand hygiene, plaque control and an externally applied antimicrobial coating. In each case, audience engagement was assessed using quantitat

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26

Tu, H., Y. N. Levchuk, and K. R. Pattipati. "Robust Action Strategies to Induce Desired Effects." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 34, no. 5 (2004): 664–80. http://dx.doi.org/10.1109/tsmca.2004.832823.

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27

Lin, Liu Hsu, Jai Yush Yen, and Fu Cheng Wang. "System Identification and Robust Control of a Pneumatic Muscle Actuator System." Applied Mechanics and Materials 284-287 (January 2013): 1936–40. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.1936.

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This paper describes the application of system identification techniques and robust control strategies to a pneumatic muscle actuator system. Due to the inherent nonlinear and time-varying characteristics of this system, it is difficult to achieve excellent performance using conventional control methods. Therefore, we apply identification techniques to model the system as linear transfer functions and regard the un-modeled dynamics as system uncertainties. Because robust control is well-known for its capability in dealing with system uncertainties, we then apply robust control strategies to gu

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28

Lin, Liu-Hsu, Jia-Yush Yen, and Fu-Cheng Wang. "ROBUST CONTROL FOR A PNEUMATIC MUSCLE ACTUATOR SYSTEM." Transactions of the Canadian Society for Mechanical Engineering 37, no. 3 (2013): 581–90. http://dx.doi.org/10.1139/tcsme-2013-0046.

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This paper presents the modeling and robust control of a pneumatic muscle actuator system. Due to the inherent nonlinear and time-varying characteristics of this system, it is difficult to achieve excellent performance using conventional control methods. Therefore, we apply identification techniques to model the system as linear transfer functions and regard the un-modeled dynamics as system uncertainties. Because H∞ robust control is well-known for its capability in dealing with system uncertainties, we then apply H∞ robust control strategies to guarantee system stability and performance for

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29

Derwent, Richard G., and Tim P. Murrells. "Are photochemical oxidant control strategies robust to the choice of chemical mechanism?" Environmental Chemistry 10, no. 3 (2013): 234. http://dx.doi.org/10.1071/en12150.

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Environmental context Throughout the world there are many places where ozone levels are elevated above internationally accepted guidelines set to protect human health. Policy makers use air quality models to formulate emission control strategies to achieve these air quality goals for ozone. There are large uncertainties in these air quality models that mask the sensitivity of the model control strategies to chemical mechanism choice. Abstract Monte Carlo sampling of pre-specified parameter ranges has been used to replace a single ‘best estimate’ photochemical trajectory model run with 11 694 ‘

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30

Rios, Hector, Romeo Falcon, Oscar A. Gonzalez, and Alejandro Dzul. "Continuous Sliding-Mode Control Strategies for Quadrotor Robust Tracking: Real-Time Application." IEEE Transactions on Industrial Electronics 66, no. 2 (2019): 1264–72. http://dx.doi.org/10.1109/tie.2018.2831191.

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31

Huang, X. Y., N. N. Yan, and R. Z. Qiu. "Dynamic models of closed-loop supply chain and robust H∞ control strategies." International Journal of Production Research 47, no. 9 (2009): 2279–300. http://dx.doi.org/10.1080/00207540701636355.

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32

Bayas, Antonio, Igor Škrjanc, and Doris Sáez. "Design of fuzzy robust control strategies for a distributed solar collector field." Applied Soft Computing 71 (October 2018): 1009–19. http://dx.doi.org/10.1016/j.asoc.2017.10.003.

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33

Kuhm, David, Dominique Knittel, and Marie-Ange Bueno. "Robust control strategies for an electric motor driven accumulator with elastic webs." ISA Transactions 51, no. 6 (2012): 732–42. http://dx.doi.org/10.1016/j.isatra.2012.05.004.

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34

Zhu, Yongxin, and Liping Fan. "On Robust Hybrid Force/Motion Control Strategies Based on Actuator Dynamics for Nonholonomic Mobile Manipulators." Journal of Applied Mathematics 2012 (2012): 1–19. http://dx.doi.org/10.1155/2012/920260.

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Robust force/motion control strategies are presented for mobile manipulators under both holonomic and nonholonomic constraints in the presence of uncertainties and disturbances. The controls are based on structural knowledge of the dynamics of the robot, and the actuator dynamics is also taken into account. The proposed control is robust not only to structured uncertainty such as mass variation but also to unstructured one such as disturbances. The system stability and the boundness of tracking errors are proved using Lyapunov stability theory. The proposed control strategies guarantee that th

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35

Van den End, Jan Willem, and Yakov Ben-Haim. "Robust Policy in Times of Pandemic." Intereconomics 56, no. 2 (2021): 108–12. http://dx.doi.org/10.1007/s10272-021-0961-1.

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AbstractThe pandemic exposes policymakers to fundamental uncertainties about future economic scenarios. While policymakers have to act forcefully to mitigate the impact on the economy, these conditions call for policy strategies that are also robust to uncertainty. This article compares two concepts of robust strategies: robust control and robust satisficing. It argues that a robust satisficing strategy is preferred and shows that the crisis responses of governments and central banks in Europe share features of robust satisficing in several dimensions.

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36

Peng, Zhaoxia, Shichun Yang, Guoguang Wen, and Ahmed Rahmani. "Distributed Consensus-Based Robust Adaptive Formation Control for Nonholonomic Mobile Robots with Partial Known Dynamics." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/670497.

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This paper investigates the distributed consensus-based robust adaptive formation control for nonholonomic mobile robots with partially known dynamics. Firstly, multirobot formation control problem has been converted into a state consensus problem. Secondly, the practical control strategies, which incorporate the distributed kinematic controllers and the robust adaptive torque controllers, are designed for solving the formation control problem. Thirdly, the specified reference trajectory for the geometric centroid of the formation is assumed as the trajectory of a virtual leader, whose informa

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37

Din, Sami Ud, Qudrat Khan, Fazal Ur Rehman, and Rini Akmeliawanti. "A Comparative Experimental Study of Robust Sliding Mode Control Strategies for Underactuated Systems." IEEE Access 6 (2018): 1927–39. http://dx.doi.org/10.1109/access.2017.2780889.

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38

Sadri, A. M., R. J. Wynne, and J. R. Wright. "Robust strategies for active vibration control of plate-like structures: Theory and experiment." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 213, no. 6 (1999): 489–504. http://dx.doi.org/10.1243/0959651991540313.

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39

Petre, Emil, Sihem Tebbani, and Dan Selişteanu. "Robust-Adaptive Control Strategies for a Time Delay Bioelectrochemical Process Using Interval Observers." Asian Journal of Control 17, no. 5 (2014): 1767–78. http://dx.doi.org/10.1002/asjc.997.

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40

Reischl, Markus, Ralf Mikut, and Georg Bretthauer. "ROBUST TRAINING AND CONTROL STRATEGIES FOR THE GRASP TYPE SELECTION OF HAND PROSTHESES." IFAC Proceedings Volumes 39, no. 16 (2006): 478–83. http://dx.doi.org/10.3182/20060912-3-de-2911.00084.

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41

Falcón, Romeo, Héctor Ríos, and Alejandro Dzul. "Comparative analysis of continuous sliding-modes control strategies for quad-rotor robust tracking." Control Engineering Practice 90 (September 2019): 241–56. http://dx.doi.org/10.1016/j.conengprac.2019.06.013.

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42

Tasoujian, Shahin, Saeed Salavati, Matthew Franchek, and Karolos Grigoriadis. "Robust IMC-PID and Parameter-varying Control Strategies for Automated Blood Pressure Regulation." International Journal of Control, Automation and Systems 17, no. 7 (2019): 1803–13. http://dx.doi.org/10.1007/s12555-018-0631-7.

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43

Din, Sami Ud, Qudrat Khan, Fazal-Ur Rehman, and Rini Akmeliawanti. "A Comparative Experimental Study of Robust Sliding Mode Control Strategies for Underactuated Systems." IEEE Access 5 (2017): 10068–80. http://dx.doi.org/10.1109/access.2017.2712261.

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44

van der Werff, Ellen, Niels van Oort, Oded Cats, and Serge Hoogendoorn. "Robust Control for Regulating Frequent Bus Service: Supporting the Implementation of Headway-Based Holding Strategies." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 9 (2019): 654–65. http://dx.doi.org/10.1177/0361198119845893.

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Reliability is a key determinant of the quality of a transit service. Control is needed to deal with the stochastic nature of high-frequency bus services and to improve service reliability. This study focuses on holding control, both schedule- and headway-based strategies. An assessment framework is developed to systematically assess the effect of different strategies on passengers, the operator, and the transport authority. This framework can be applied by operators or authorities to determine which holding strategy is most beneficial to regulate headways, and thus solve related problems. In

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45

Sheikh, M. R. I., R. Takahashi, and J. Tamura. "Robust Stabilizing Controllers to Automatic Generation Control for Load Frequency Control Application." Journal of Scientific Research 2, no. 2 (2010): 285–93. http://dx.doi.org/10.3329/jsr.v2i2.3063.

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Since superconducting magnetic energy storage (SMES) unit with a self-commutated converter is capable of controlling both the active and reactive powers simultaneously and quickly, increasing attention has been focused recently on power system stabilization by SMES control. This study presents the effects of novel control strategies of self-tuned fuzzy proportional integral (FPI) controller and fuzzy frequency (FF) controller associated with the automatic generation control (AGC) including SMES unit. The effects of the self-tuning configuration with FPI controller in AGC is also compared with

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46

Zhang, Longge. "Automatic Offline Formulation of Robust Model Predictive Control Based on Linear Matrix Inequalities Method." Abstract and Applied Analysis 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/380105.

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Two automatic robust model predictive control strategies are presented for uncertain polytopic linear plants with input and output constraints. A sequence of nested geometric proportion asymptotically stable ellipsoids and controllers is constructed offline first. Then the feedback controllers are automatically selected with the receding horizon online in the first strategy. Finally, a modified automatic offline robust MPC approach is constructed to improve the closed system's performance. The new proposed strategies not only reduce the conservatism but also decrease the online computation. Nu

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47

Chen, Chunlin, Lin-Cheng Wang, and Yuanlong Wang. "Closed-Loop and Robust Control of Quantum Systems." Scientific World Journal 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/869285.

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For most practical quantum control systems, it is important and difficult to attain robustness and reliability due to unavoidable uncertainties in the system dynamics or models. Three kinds of typical approaches (e.g., closed-loop learning control, feedback control, and robust control) have been proved to be effective to solve these problems. This work presents a self-contained survey on the closed-loop and robust control of quantum systems, as well as a brief introduction to a selection of basic theories and methods in this research area, to provide interested readers with a general idea for

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48

Klocke, Fritz, Stephan Kratz, Thomas Auerbach, Sascha Gierlings, Guido Wirtz, and Dražen Veselovac. "Process Monitoring and Control of Machining Operations." International Journal of Automation Technology 5, no. 3 (2011): 403–11. http://dx.doi.org/10.20965/ijat.2011.p0403.

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In today’s production, the overall technical aim of a monitoring and control system is to introduce robust manufacturing with maximum performance. Generating targeted values means to transfer production know-how to the application of monitoring and control strategies, whereas such systems include a decisive potential for increasing added value in production companies. Especially in complex processes, important operational sequences should be analyzed and optimized online by means of system analysis and control. This paper reviews certain aspects and introduces recent investigations on process

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49

Kärkkäinen, Tommi, and Erkki Heikkola. "Robust Formulations for Training Multilayer Perceptrons." Neural Computation 16, no. 4 (2004): 837–62. http://dx.doi.org/10.1162/089976604322860721.

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The connection between robust statistical estimates and nonsmooth optimization is established. Based on the resulting family of optimization problems, robust learning problem formulations with regularization-based control on the model complexity of the multilayer perceptron network are described and analyzed. Numerical experiments for simulated regression problems are conducted, and new strategies for determining the regularization coefficient are proposed and evaluated.

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50

El Karaoui, Imane, Mohammed Maaroufi, and Badre Bossoufi. "Robust power control methods for wind turbines using DFIG-generator." International Journal of Power Electronics and Drive Systems (IJPEDS) 10, no. 4 (2019): 2101. http://dx.doi.org/10.11591/ijpeds.v10.i4.pp2101-2117.

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<span>The purpose of this work is to present the advantages of the power control (active and reactive) of a wind energy system in order to improve the quality of the energy produced to the grid by presenting two control strategies applied to the conversion system of wind energy equipped with an asynchronous generator with dual power supply. Both techniques are studied and developed and consist of a field control (FOC) and a sliding mode control. They find their strongest justifications for the problem of using a nonlinear control law that is robust to the uncertainties of the model. The

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