Relevant bibliographies by topics / Varying control

Academic literature on the topic 'Varying control'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Varying control"

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IBA, Daisuke, and JR SPENCER. "1C21 Vibration Control using Harmonically-varying Damping." Proceedings of the Symposium on the Motion and Vibration Control 2010 (2010): _1C21–1_—_1C21–10_. http://dx.doi.org/10.1299/jsmemovic.2010._1c21-1_.

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Kim, Dongho, Youngjin Park, and Youn-sik Park. "2C14 Varying Horizon LQ Control for Vehicle Attitude Control in Rear-end Collisions." Proceedings of the Symposium on the Motion and Vibration Control 2010 (2010): _2C14–1_—_2C14–6_. http://dx.doi.org/10.1299/jsmemovic.2010._2c14-1_.

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Imsland, L., and J. A. Rossiter. "TIME VARYING TERMINAL CONTROL." IFAC Proceedings Volumes 38, no. 1 (2005): 447–52. http://dx.doi.org/10.3182/20050703-6-cz-1902.00936.

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Bryson, A. E. "Time-Varying Linear-Quadratic Control." Journal of Optimization Theory and Applications 100, no. 3 (March 1999): 515–25. http://dx.doi.org/10.1023/a:1022682305644.

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Barabanov, Andrey E., and Andrey Ghulchak. "DELAYED TIME-VARYING H∞ CONTROL DESIGN." IFAC Proceedings Volumes 38, no. 1 (2005): 365–70. http://dx.doi.org/10.3182/20050703-6-cz-1902.00922.

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Podsędkowski, Leszek, Piotr Wróblewski, and Marcin Zawierucha. "Telemanipulator Control with Varying Camera Position." Solid State Phenomena 198 (March 2013): 275–80. http://dx.doi.org/10.4028/www.scientific.net/ssp.198.275.

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Technical University of Lodz in cooperation with the Foundation for Cardiac Surgery Development conducts research on the design and control method of Polish Robin Heart cardiosurgical robots family. One of the major problems in telemanipulation is intuitiveness of control. One of the methods to ensure it is using systems that duplicate master displacement to manipulator displacement. The selection of the proper method when it is not possible to predict what will be the position of the camera observing the work area in relation to the position of the manipulator arm is especially important. Transformations between different coordinate systems must be taken into consideration. Four methods of position copying system implementation tested on RobIn Heart cardiosurgical telemanipulator will be presented in this article. Detailed algorithms will be described and the results of tests determining the duration of certain tasks will be presented.
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IBA, Daisuke, and Billie F. SPENCER JR. "Vibration Control using Harmonically-Varying Damping." Journal of System Design and Dynamics 5, no. 5 (2011): 727–36. http://dx.doi.org/10.1299/jsdd.5.727.

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Kamen, E. W., P. P. Khargonekar, and A. Tannenbaum. "Control of slowly-varying linear systems." IEEE Transactions on Automatic Control 34, no. 12 (1989): 1283–85. http://dx.doi.org/10.1109/9.40776.

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Kishore, W. C. Arun, S. Sen, G. Ray, and T. K. Ghoshal. "Dynamic Control Allocation for Tracking Time-Varying Control Demand." Journal of Guidance, Control, and Dynamics 31, no. 4 (July 2008): 1150–57. http://dx.doi.org/10.2514/1.34085.

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Koike, Shigeaki. "On the Bellman equations with varying control." Bulletin of the Australian Mathematical Society 53, no. 1 (February 1996): 51–62. http://dx.doi.org/10.1017/s0004972700016713.

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The value function is presented by minimisation of a cost functional over admissible controls. The associated first order Bellman equations with varying control are treated. It turns out that the value function is a viscosity solution of the Bellman equation and the comparison principle holds, which is an essential tool in obtaining the uniqueness of the viscosity solutions.
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Dissertations / Theses on the topic "Varying control"

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Ramos, Fuentes Germán Andrés. "Digital repetitive control under varying frequency conditions." Doctoral thesis, Universitat Politècnica de Catalunya, 2012. http://hdl.handle.net/10803/96769.

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The tracking/rejection of periodic signals constitutes a wide field of research in the control theory and applications area and Repetitive Control has proven to be an efficient way to face this topic; however, in some applications the period of the signal to be tracked/rejected changes in time or is uncertain, which causes and important performance degradation in the standard repetitive controller. This thesis presents some contributions to the open topic of repetitive control working under varying frequency conditions. These contributions can be organized as follows: One approach that overcomes the problem of working under time varying frequency conditions is the adaptation of the controller sampling period, nevertheless, the system framework changes from Linear Time Invariant to Linear Time-Varying and the closed-loop stability can be compromised. This work presents two different methodologies aimed at analysing the system stability under these conditions. The first one uses a Linear Matrix Inequality (LMI) gridding approach which provides necessary conditions to accomplish a sufficient condition for the closed-loop Bounded Input Bounded Output stability of the system. The second one applies robust control techniques in order to analyse the stability and yields sufficient stability conditions. Both methodologies yield a frequency variation interval for which the system stability can be assured. Although several approaches exist for the stability analysis of general time-varying sampling period controllers few of them allow an integrated controller design which assures closed-loop stability under such conditions. In this thesis two design methodologies are presented, which assure stability of the repetitive control system working under varying sampling period for a given frequency variation interval: a mu-synthesis technique and a pre-compensation strategy. On a second branch, High Order Repetitive Control (HORC) is mainly used to improve the repetitive control performance robustness under disturbance/reference signals with varying or uncertain frequency. Unlike standard repetitive control, the HORC involves a weighted sum of several signal periods. With a proper selection of the associated weights, this high order function offers a characteristic frequency response in which the high gain peaks located at harmonic frequencies are extended to a wider region around the harmonics. Furthermore, the use of an odd-harmonic internal model will make the system more appropriate for applications where signals have only odd-harmonic components, as in power electronics systems. Thus an Odd-harmonic High Order Repetitive Controller suitable for applications involving odd-harmonic type signals with varying/uncertain frequency is presented. The open loop stability of internal models used in HORC and the one presented here is analysed. Additionally, as a consequence of this analysis, an Anti-Windup (AW) scheme for repetitive control is proposed. This AW proposal is based on the idea of having a small steady state tracking error and fast recovery once the system goes out of saturation. The experimental validation of these proposals has been performed in two different applications: the Roto-magnet plant and the active power filter application. The Roto-magnet plant is an experimental didactic plant used as a tool for analysing and understanding the nature of the periodic disturbances, as well as to study the different control techniques used to tackle this problem. This plant has been adopted as experimental test bench for rotational machines. On the other hand, shunt active power filters have been widely used as a way to overcome power quality problems caused by nonlinear and reactive loads. These power electronics devices are designed with the goal of obtaining a power factor close to 1 and achieving current harmonics and reactive power compensation.
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Rice, Michael D. (Michael David). "Adaptive error control over slowly varying channels." Diss., Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/13396.

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李泉志 and Chuen-chi Lee. "The control of a varying gain process using a varying sampling-rate PID controller with application to pH control." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31211598.

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Lee, Chuen-chi. "The control of a varying gain process using a varying sampling-rate PID controller with application to pH control /." [Hong Kong] : University of Hong Kong, 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1366573X.

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Mills, Russell Edward. "Robust backstepping control of nonlinear uncertain systems." Thesis, University of Sheffield, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246989.

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Lane, Steven. "Time average feedforward control techniques for time varying systems." Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-06082009-170722/.

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Carter, Lance Huntington. "Linear parameter varying representations for nonlinear control design /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Jerbi, Ali. "Adaptive control of time-varying discrete-time systems." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/15743.

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Petkos, Georgios. "Learning dynamics for robot control under varying contexts." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/3130.

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High fidelity, compliant robot control requires a sufficiently accurate dynamics model. Often though, it is not possible to obtain a dynamics model sufficiently accurately or at all using analytical methods. In such cases, an alternative is to learn the dynamics model from movement data. This thesis discusses the problems specific to dynamics learning for control under nonstationarity of the dynamics. We refer to the cause of the nonstationarity as the context of the dynamics. Contexts are, typically, not directly observable. For instance, the dynamics of a robot manipulator changes as the robot manipulates different objects and the physical properties of the load – the context of the dynamics – are not directly known by the controller. Other examples of contexts that affect the dynamics are changing force fields or liquids with different viscosity in which a manipulator has to operate. The learned dynamics model needs to be adapted whenever the context and therefore the dynamics changes. Inevitably, performance drops during the period of adaptation. The goal of this work, is to reuse and generalize the experience obtained by learning the dynamics of different contexts in order to adapt to changing contexts fast. We first examine the case that the dynamics may switch between a discrete, finite set of contexts and use multiple models and switching between them to adapt the controller fast. A probabilistic formulation of multiple models is used, where a discrete latent variable is used to represent the unobserved context and index the models. In comparison to previous multiple model approaches, the developed method is able to learn multiple models of nonlinear dynamics, using an appropriately modified EM algorithm. We also deal with the case when there exists a continuum of possible contexts that affect the dynamics and hence, it becomes essential to generalize from a set of experienced contexts to novel contexts. There is very little previous work on this direction and the developed methods are completely novel. We introduce a set of continuous latent variables to represent context and introduce a dynamics model that depends on this set of variables. We first examine learning and inference in such a model when there is strong prior knowledge on the relationship of these continuous latent variables to the modulation of the dynamics, e.g., when the load at the end effector changes. We also develop methods for the case that there is no such knowledge available. Finally, we formulate a dynamics model whose input is augmented with observed variables that convey contextual information indirectly, e.g., the information from tactile sensors at the interface between the load and the arm. This approach also allows generalization to not previously seen contexts and is applicable when the nature of the context is not known. In addition, we show that use of such a model is possible even when special sensory input is not available by using an instance of an autoregressive model. The developed methods are tested on realistic, full physics simulations of robot arm systems including a simplistic 3 degree of freedom (DOF) arm and a simulation of the 7 DOF DLR light weight robot arm. In the experiments, varying contexts are different manipulated objects. Nevertheless, the developed methods (with the exception of the methods that require prior knowledge on the relationship of the context to the modulation of the dynamics) are more generally applicable and could be used to deal with different context variation scenarios.
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Kaipio, Tero. "Control of machine drives for varying inertia systems." Thesis, University of Wolverhampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.325980.

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Books on the topic "Varying control"

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Ilchmann, Joachim. Contributions to time-varying linear control systems. Ammersbek bei Hamburg: Verlag an der Lottbek, 1989.

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Shin, Jong-Yeob. Linear parameter varying control for actuator failure. Hampton, VA: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 2002.

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1953-, Ioannou P. A., ed. Linear time-varying systems: Control and adaptation. Englewood Cliffs, N.J: Prentice Hall, 1993.

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Ramos, Germán A., Ramon Costa-Castelló, and Josep M. Olm. Digital Repetitive Control under Varying Frequency Conditions. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37778-5.

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Sename, Olivier, Peter Gaspar, and József Bokor, eds. Robust Control and Linear Parameter Varying Approaches. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36110-4.

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Peters, Marc A., and Pablo A. Iglesias. Minimum Entropy Control for Time-Varying Systems. Boston, MA: Birkhäuser Boston, 1997. http://dx.doi.org/10.1007/978-1-4612-1982-8.

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White, Andrew P., Guoming Zhu, and Jongeun Choi. Linear Parameter-Varying Control for Engineering Applications. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5040-4.

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Peters, Marc A. Minimum Entropy Control for Time-Varying Systems. Boston, MA: Birkhäuser Boston, 1997.

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1964-, Iglesias Pablo A., ed. Minimum entropy control for time-varying systems. Boston: Birkhäuser, 1997.

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Kaipio, Tero. Control of machine drives for varying inertia systems. Wolverhampton: University of Wolverhampton, 2000.

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Book chapters on the topic "Varying control"

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Howlett, Philip G., and Peter J. Pudney. "Continuously Varying Gradient." In Advances in Industrial Control, 267–84. London: Springer London, 1995. http://dx.doi.org/10.1007/978-1-4471-3084-0_13.

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Ge, Zhiqiang, and Zhihuan Song. "Time-Varying Process Monitoring." In Advances in Industrial Control, 81–94. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4513-4_7.

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Bouthellier, P. R., and B. K. Ghosh. "Simultaneous Stabilization of Linear Time Varying Systems by Linear Time Varying Compensation." In Computation and Control, 1–9. Boston, MA: Birkhäuser Boston, 1989. http://dx.doi.org/10.1007/978-1-4612-3704-4_1.

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Bourlès, Henri, and Bogdan Marinescu. "Open-Loop Control by Model-Matching." In Linear Time-Varying Systems, 523–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19727-7_10.

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Mzyk, Grzegorz. "Time-Varying Systems." In Lecture Notes in Control and Information Sciences, 171–80. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03596-3_8.

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Ramos, Germán A., Ramon Costa-Castelló, and Josep M. Olm. "Repetitive Control." In Digital Repetitive Control under Varying Frequency Conditions, 5–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37778-5_2.

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Bourlès, Henri, and Bogdan Marinescu. "Closed-Loop Control by Output Feedback Pole Placement." In Linear Time-Varying Systems, 545–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19727-7_11.

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Blanchini, Franco, and Stefano Miani. "Control of parameter-varying systems." In Set-Theoretic Methods in Control, 235–69. Boston, MA: Birkhäuser Boston, 2008. http://dx.doi.org/10.1007/978-0-8176-4606-6_7.

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Blanchini, Franco, and Stefano Miani. "Control of parameter-varying systems." In Set-Theoretic Methods in Control, 289–335. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17933-9_7.

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Tomás-Rodríguez, María, and Stephen P. Banks. "Optimal Control." In Linear, Time-varying Approximations to Nonlinear Dynamical Systems, 101–21. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-101-1_6.

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Conference papers on the topic "Varying control"

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Shi, Fengming, and Ron J. Patton. "Low eigenvalue sensitivity eigenstructure assignment to linear parameter varying systems." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334624.

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Sun, Jian, Jie Chen, and G. P. Liu. "New stability criteria for linear systems with time-varying interval delay." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334634.

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Xu, Sheng, Minrui Fei, Dajun Du, and Liqin Wu. "Output control of TCP/AQM network system with time-varying delay." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737626.

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Mutoh, Yasuhiko, Masakatsu Kemmotsu, and Wataru Akutsu. "Time-varying observer based discrete control for 2-link robot manipulator." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737636.

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Kamali, Marzieh, Javad Askari, Farid Sheikholeslam, and Ali Khaki Sedigh. "Robust adaptive actuator failure compensation controller for systems with unknown time-varying state delays." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334598.

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Qin, Chen, Zhengrong Xiang, and Hamid Reza Karimi. "Robust fault detection for switched systems with time-varying delay using delta operator approach." In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915130.

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Maghenem, Mohamed, Hermann Lekefouet, Antonio Loria, and Elena Panteley. "Decentralized synchronization of time-varying oscillators under time-varying bidirectional graphs." In 2019 American Control Conference (ACC). IEEE, 2019. http://dx.doi.org/10.23919/acc.2019.8815146.

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Mutoh, Yasuhiko, and Tomohiro Hara. "Stability of the observer-based pole placement for discrete time-varying non-lexicographically-fixed systems." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334635.

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Zhong, Wei-Song, and Guo-Ping Liu. "Global controlled consensus of multi-agent systems with different agent dynamics and time-varying communication delay." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334711.

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Shu, Xinyu, Pablo Ballesteros, and Christian Bohn. "LPV gain-scheduling control with time-varying sampling time for rejecting nonstationary harmonically related multisine disturbances." In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915117.

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Reports on the topic "Varying control"

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Pearson, Allan E. Control and Identification of Time Varying Systems. Fort Belvoir, VA: Defense Technical Information Center, October 1986. http://dx.doi.org/10.21236/ada177567.

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Pearson, A. E. Control and Identification of Time Varying Systems. Fort Belvoir, VA: Defense Technical Information Center, July 1985. http://dx.doi.org/10.21236/ada159067.

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Matei, Ion, Assane Gueye, and John S. Baras. Flow Control in Time-Varying, Random Supply Chains. Gaithersburg, MD: National Institute of Standards and Technology, January 2013. http://dx.doi.org/10.6028/nist.ir.7907.

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Meirovitch, Leonard. Control of Large Space Structures with Varying Configuration. Fort Belvoir, VA: Defense Technical Information Center, March 1993. http://dx.doi.org/10.21236/ada265764.

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Psiaki, Mark L., and Raffaello D'Andrea. Satellite Attitude Control Using Magnetic Torquers, a Periodic Time-Varying Control Problem. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada373391.

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Siegmund, David. Change-Point Detection and Adaptive Control of Time-Varying Systems. Fort Belvoir, VA: Defense Technical Information Center, September 1993. http://dx.doi.org/10.21236/ada273509.

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Shrader, Brooke, Armen Babikyan, Nathaniel M. Jones, Thomas H. Shake, and Andrew P. Worthen. Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity. Fort Belvoir, VA: Defense Technical Information Center, December 2010. http://dx.doi.org/10.21236/ada540462.

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Buche, Robert, and Harold J. Kushner. Stability and Control of Mobile Communications Systems With Time Varying Channels. Fort Belvoir, VA: Defense Technical Information Center, August 2001. http://dx.doi.org/10.21236/ada461863.

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Buche, Robert, and Harold J. Kushner. Control of Mobile Communication Systems With Time-Varying Channels via Stability Methods. Fort Belvoir, VA: Defense Technical Information Center, August 2003. http://dx.doi.org/10.21236/ada461517.

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Kushner, Harold J. Scheduling and Control of Mobile Communications Networks with Randomly Time Varying Channels by Stability Methods. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada458950.

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