Relevant bibliographies by topics / Tracking control

Academic literature on the topic 'Tracking control'

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Published: 4 June 2021
Last updated: 21 February 2023

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Journal articles on the topic "Tracking control"

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XING, YIFAN. "TRACKING CONTROL OF QUANTUM VON NEUMANN ENTROPY." International Journal of Psychosocial Rehabilitation 24, no. 04 (February 28, 2020): 880–87. http://dx.doi.org/10.37200/ijpr/v24i4/pr201061.

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Olejár, M., V. Cviklovič, D. Hrubý, and O. Lukáč. "Autonomous control of biaxial tracking photovoltaic system." Research in Agricultural Engineering 61, Special Issue (June 2, 2016): S48—S52. http://dx.doi.org/10.17221/29/2015-rae.

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Tracking photovoltaic systems maximize solar energy on the photovoltaic cells surface in order to maximize the energy gain at a given moment. Energy gain is dependent on the accuracy of photovoltaic cells direction, control method and tracking period. The control of tracking systems is based on theoretical calculations of sun position for a specific position in specific time. Designed control algorithm of the biaxial tracking photovoltaic system is able of autonomous navigation directed to the sun without knowing the position. It is based on the sun position sensor. The designed solution increases the solar gain by 33.8% in comparison with stable photovoltaic systems. It is usable in the research focused on the control method of step-controlled biaxial tracking photovoltaic devices.
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Ogata, Tokoku, Naohide Sakimura, Tatsuya Nakazaki, Kiyoshi Ohishi, Toshimasa Miyazaki, Daiichi Koide, Haruki Tokumaru, and Yoshimichi Takano. "Tracking Control System with Equivalent Perfect Tracking Control for Optical Disks." IEEJ Transactions on Industry Applications 132, no. 12 (2012): 1121–30. http://dx.doi.org/10.1541/ieejias.132.1121.

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Youssef, Ayman, Mohamed El Telbany, and Abdelhalim Zekry. "Reinforcement Learning for Online Maximum Power Point Tracking Control." Journal of Clean Energy Technologies 4, no. 4 (2015): 245–48. http://dx.doi.org/10.7763/jocet.2016.v4.290.

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Gierlak, Piotr, and Wiesław Żylski. "Tracking Control of Manipulator." IFAC Proceedings Volumes 42, no. 13 (2009): 623–28. http://dx.doi.org/10.3182/20090819-3-pl-3002.00108.

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FUNAHASHI, YASUYUKI, and HISAO KATOH. "Robust-tracking deadbeat control." International Journal of Control 56, no. 1 (July 1992): 213–25. http://dx.doi.org/10.1080/00207179208934310.

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Stanković, S. S., D. M. Stipanović, and M. S. Stanković. "Decentralized overlapping tracking control." International Journal of General Systems 43, no. 3-4 (March 4, 2014): 282–93. http://dx.doi.org/10.1080/03081079.2014.883713.

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Grujić, Ljubomir T., and William Pratt Mounfield. "Natural tracking PID process control for exponential tracking." AIChE Journal 38, no. 4 (April 1992): 555–62. http://dx.doi.org/10.1002/aic.690380409.

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Moon, Jung-Hwan, Jang-Heon Kim, Il-Du Kim, Jung-Joon Kim, and Bum-Man Kim. "Gate-Bias Control Technique for Envelope Tracking Doherty Power Amplifier." Journal of Korean Institute of Electromagnetic Engineering and Science 19, no. 8 (August 31, 2008): 807–13. http://dx.doi.org/10.5515/kjkiees.2008.19.8.807.

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Lu, Ping. "Tracking Control of Nonlinear Systems with Bounded Controls and Control Rates." IFAC Proceedings Volumes 29, no. 1 (June 1996): 2307–12. http://dx.doi.org/10.1016/s1474-6670(17)58017-9.

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Dissertations / Theses on the topic "Tracking control"

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Long, Matthew Robert. "Spacecraft Attitude Tracking Control." Thesis, Virginia Tech, 1999. http://hdl.handle.net/10919/33843.

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The problem of reorienting a spacecraft to acquire a moving target is investigated. The spacecraft is modeled as a rigid body with N axisymmetric wheels controlled by axial torques, and the kinematics are represented by Modified Rodriques Parameters. The trajectory, denoted the reference trajectory, is one generated by a virtual spacecraft that is identical to the actual spacecraft. The open-loop reference attitude, angular velocity, and angular acceleration tracking commands are constructed so that the solar panel vector is perpendicular to the sun vector during the tracking maneuver. We develop a nonlinear feedback tracking control law, derived from Lyapunov stability and control theory, to provide the control torques for target tracking. The controller makes the body frame asymptotically track the reference motion when there are initial errors in the attitude and angular velocity. A spacecraft model, based on the X-ray Timing Explorer spacecraft, is used to demonstrate the effectiveness of the Lyapunov controller in tracking a given target.
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Ramírez, Eduardo Díaz. "A MORE EFFICIENT TRACKING SYSTEM FOR THE SANTIAGO SATELLITE TRACKING STATION." International Foundation for Telemetering, 2007. http://hdl.handle.net/10150/604559.

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ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada
A digital antenna control system has been designed and installed on a pedestal that was formerly used to drive a VHF array and that has now been replaced with an 11 meter S-Band parabolic reflector. In this Paper, the former analog tracking system will be described, showing all the drawbacks that made it unusable for S-Band. Subsequently, the development and implementation of the digital S-Band tracking system, using Labview, C++ & digital control theory will be discussed. Finally, there will be a comparison between the digital and analog system, too.
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Sakurama, Kazunori. "Trajectory Tracking Control of Hamiltonian and Hybrid Control Systems." 京都大学 (Kyoto University), 2004. http://hdl.handle.net/2433/147576.

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Wang, Ning. "Model-Free Optimized Tracking Control Heuristic." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40911.

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Tracking control algorithms often target the convergence of a tracking error. However, this can be at the expense of other important system characteristics, such as the control effort used to annihilate the tracking error, transient response, or steady-state characteristics, for example. Furthermore, most tracking control methods assume prior knowledge of the system dynamics, which is not always a realistic assumption, especially in the case of highly complex systems. In this thesis, a model-free optimized tracking control architectural heuristic is proposed. The suggested feedback system is composed of two control loops. The first is the tracking loop. It focuses on the convergence of the tracking error. It is implemented using two different model-free control algorithms for comparison purpose: Reinforcement Learning (RL) and the Nonlinear Threshold Accepting (NLTA) technique. The RL scheme reformulates the tracking error combinations into a form of Markov-Decision-Process (MDP) and applies Q-Learning to build the best tracking control policy for the dynamic system under consideration. On the other hand, the NLTA algorithm is applied to tune the gains of a PID controller. The second control loop is in the form of a nonlinear state feedback loop. It is implemented using a feedforward artificial neural network (ANN) to optimize a system-wide cost function which can be flexible enough to encompass a set of desired design requirements pertaining to the targeted system behavior. This may include, for instance, the target overshoot, settling time, rise time, etc. The proposed architectural heuristic provides a model-free framework to tackle such control problems, in the sense that the plant's dynamic model is not required to be known in advance. Yet, at least a subset of the stability region of the optimized gains has to be known in advance so that it can provide a search space for the optimization algorithms. Simulation results on two dynamic systems demonstrate the superiority of the proposed control scheme.
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Keller, Joseph J. "Tracking control of autonomous underwater vehicles." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02Dec%5FKeller.pdf.

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Thesis (Mechanical Engineer and M.S. in Mechanical Engineering)--Naval Postgraduate School, December 2002.
Thesis advisor(s): Anthony J. Healey. Includes bibliographical references (p. 67-68). Also available online.
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Liu, Yong. "NEURAL ADAPTIVE NONLINEAR TRACKING USING TRAJECTORY LINEARIZATION." Ohio University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1177092159.

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Salai, Robert. "Tracking of Head Movements for Motion Control." Thesis, Norwegian University of Science and Technology, Department of Engineering Cybernetics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9901.

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The capture of gestures in order to use them as input for intuitive control has been investigated exhaustively in recent years. However, for the most part this has resulted in relatively expensive devices. The contribution of this report is the investigation on the feasibility of the development of a low-cost vision based input device for the tracking of head movements, concerning the use of them for motion control. The input device relies on the infrared camera, along with the built-in image analysis tools, present on a Nintendo Wii remote for the measurement of the location and orientation of a head-mountable marker. The marker consists of a set of optical feature points which are easily detectable, and organized in a fashion which allows for the determination of its position and orientation in space. The developed input device was then evaluated in order to determine the operating range, accuracy and robustness, and was shown to be feasible for its intended use. Finally, the implemented device was utilized to control a mechanical output device, being a unit capable of panning and tilting.

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Yao, Liqun. "Robust nonlinear tracking control of robotic manipulators." Thesis, University of Leicester, 1999. http://hdl.handle.net/2381/30175.

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This thesis has discussed the development and implementation of robust nonlinear tracking control for a parallel and serial topology Tetrahedral robot (Tetrabot), although the theoretical control strategy presented is applicable to any manipulator tracking problem. The design of robust tracking controllers involves deriving a tracking law for uncertain dynamic systems, such that the actual positions closely track desired trajectories. Two new schemes, a robust sliding mode control and a Lyapunov-based robust tracking control, have been presented for uncertain dynamical systems in the presence of model uncertainty and disturbances. The foci of this study are the concepts and techniques of robust nonlinear tracking control with a bias toward industrial applications. The Tetrabot system structure, hardware, software and the results of implementation on the three degree of freedom parallel geometry have been studied. In order to implement robust tracking control laws, the Tetrabot system software has been further developed. Most importantly, the results of implementation of a nonlinear tracking controller on the Tetrabot rig facility are also studied. To demonstrate the performance attainable by this control strategy, the trajectory involved movement across the primary working volume to the end-effect point which is the largest distance possible and involved the continuous motion; such a motion will invoke a wide range of possible nonlinear dynamic representations. The proposed control strategy is robust to variations in robot loading. The experimental results obtained for the closed-loop response indicate that compensation, which employs explicit off-line parameter estimation, can improve tracking accuracy significantly. Using the robust tracking controllers, the position errors were smaller than those obtained using the original PID controllers. The robust tracking controller showed excellent results.
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Hitchings, Mark R., and n/a. "Distance and Tracking Control for Autonomous Vehicles." Griffith University. School of Microelectronic Engineering, 1999. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20050902.084155.

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The author's concept of the distance and tracking control problem for autonomous vehicles relates to the cooperative behaviour of two successive vehicles travelling in the same environment. This behaviour requires one vehicle, designated the leader to move autonomously around it's environment with other vehicles, designated followers maintaining a coincident travel path and desired longitudinal distance with respect to the leader. Distance and tracking control is beneficial in numerous applications including guiding autonomous vehicles in Intelligent Transport Systems (ITS) which increases traffic safety and the capacity of pre-existing road infrastructure. Service robotics may also benefit from the cost savings and flexibility offered by distance and tracking control which enables a number of robots to cooperate together in order to achieve a task beyond the capabilities ofjust one robot. Using a distance and tracking control scheme an intelligent leader robot may guide a number of less intelligent (and therefore less costly and less complex) followers to a work-site to perform a task. The author's approach to the distance and tracking control problem consisted of two separate solutions - an initial solution used as a starting point and learning experience and a second, more robust, fuzzy control-based solution. This thesis briefly describes the initial solution, but places a greater emphasis on the second solution. The reason for this is that the fuzzy control-based solution offers significant improvement on the initial solution and was developed based on conclusions drawn from the initial solution. Most implementations of distance and tracking control, sometimes referred to as Intelligent Cruise Control (ICC) or platooning, are limited to longitudinal distance control only. The leader tracking control is performed either implicitly by a separate lane-following control system or by human drivers. The fuzzy control-based solution offered in this thesis performs both distance and tracking control of an autonomous follower vehicle with respect to a leader vehicle in front of it. It represents a simple and cost effective solution to the requirements of autonomous vehicles operating in ITS schemes - particularly close formation platooning. The follower tracks a laser signal emitted by the leader and monitors the distance to the follower at the same time using ultrasonic ranging techniques. The follower uses the data obtained from these measuring techniques as inputs to a fuzzy controller algorithm to adjust its distance and alignment with respect to the leader. Other systems employed on road vehicles utilise video-based leader tracking, or a range of lane-following methods such as magnetometer or video-based methods. Typically these methods are disadvantaged by substantial unit and/or infrastructure costs associated with their deployment. The limitations associated with the solutions presented in this thesis arise in curved trajectories at larger longitudinal distance separations between vehicles. The effects of these limitations on road vehicles has yet to be fully quantified, however it is thought that these effects would not disadvantage its use in close formation platooning. The fuzzy control-based distance and tracking control solution features two inputs, which are the distance and alignment of the follower with respect to the leader. The fuzzy controller asserts two outputs, which are left and right wheel velocities to control the speed and trajectory of a differential drive vehicle. Each of the input and output fuzzy membership functions has seven terms based around lambda, Z-type and S-type functions. The fuzzy rule base consists of 49 rules and the fuzzy inference stage is based on the MAX/MIN method. A Centre of Maximum (CoM) def'uzzification method is used to provide the two crisp valued outputs to the vehicle motion control. The methods chosen for the fuzzy control of distance and tracking for autonomous vehicles were selected based on a compromise between their computational complexity and performance characteristics. This compromise was necessary in order to implement the chosen controller structure on pre-existing hardware test beds based on an 8-bit microcontrollers with limited memory and processing resources. Overall the fuzzy control-based solution presented in this thesis effectively solves the distance and tracking control problem. The solution was applied to differential drive hardware test-beds and was tested to verify performance. The solution was thoroughly tested in both the simulation environment and on hardware test-beds. Several issues are identified in this thesis regarding the application of the solution to other platforms and road vehicle use. The solution will be shown to be directly portable to service robotics applications and, with minor modifications, applicable to road vehicle close-formation platooning.
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Sever, Manfred D. M. "Tip velocity tracking control for elastic manipulators." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0014/NQ35318.pdf.

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Books on the topic "Tracking control"

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Qu, Zhihua. Robust tracking control of robot manipulators. New York: IEEE Press, 1996.

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North Atlantic Treaty Organization. Advisory Group for Aerospace Research and Development. Pointing and tracking systems. Neuilly-sur-Seine, France: AGARD, 1994.

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Sever, Manfred D. M. Tip velocity tracking control for elastic manipulators. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1998.

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Model-based tracking control of nonlinear systems. Boca Raton: Chapman and Hall/CRC, 2012.

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Jing, Zhongliang, Han Pan, Yuankai Li, and Peng Dong. Non-Cooperative Target Tracking, Fusion and Control. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-90716-1.

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Choi, Youngjin, and Wan Kyun Chung, eds. PID Trajectory Tracking Control for Mechanical Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-40041-7.

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Li, Meng, Yong Chen, and Ikram Ali. Tracking Control of Networked Systems via Sliding-Mode. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6514-1.

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Six Sigma Financial Tracking and Reporting. New York: McGraw-Hill, 2006.

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Brian, McKibben, and McCarty Tom, eds. Six sigma financial tracking and reporting. New York: McGraw-Hill, 2005.

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Lamon, Pierre. 3D-position tracking and control for all-terrain robots. Berlin: Springer, 2008.

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Book chapters on the topic "Tracking control"

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Frank, Steven A. "Tracking." In Control Theory Tutorial, 63–67. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91707-8_8.

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Gans, Roger F. "Tracking Control." In Mechanical Systems, 361–93. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08371-1_10.

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Ortega, Romeo, Antonio Loría, Per Johan Nicklasson, and Hebertt Sira-Ramírez. "Trajectory tracking control." In Passivity-based Control of Euler-Lagrange Systems, 93–113. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-3603-3_4.

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Skowronski, Janislaw M. "Adaptive Tracking Control." In Control of Nonlinear Mechanical Systems, 323–67. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-3722-9_7.

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Isidori, Alberto. "Tracking and Regulation." In Nonlinear Control Systems, 387–425. London: Springer London, 1995. http://dx.doi.org/10.1007/978-1-84628-615-5_8.

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Zhang, Chunlei, and Raúl Ordóñez. "Swarm Tracking." In Extremum-Seeking Control and Applications, 155–97. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2224-1_8.

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Trentelman, Harry L., Anton A. Stoorvogel, and Malo Hautus. "Tracking and regulation." In Communications and Control Engineering, 195–209. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0339-4_9.

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Kiong, Tan Kok, Lee Tong Heng, Dou Huifang, and Huang Sunan. "Precision Tracking Motion Control." In Advances in Industrial Control, 13–74. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-3691-0_2.

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Scaglia, Gustavo, Mario Emanuel Serrano, and Pedro Albertos. "Introduction to Tracking Control." In Linear Algebra Based Controllers, 1–8. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42818-1_1.

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Hackl, Christoph M. "Adaptive $$\lambda $$ -Tracking Control." In Non-identifier Based Adaptive Control in Mechatronics, 169–215. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55036-7_8.

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Conference papers on the topic "Tracking control"

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Gershon, E. "Delayed Systems - H∞ Preview Tracking Control." In 2018 UKACC 12th International Conference on Control (CONTROL). IEEE, 2018. http://dx.doi.org/10.1109/control.2018.8516863.

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Yang, Z.-Jiang, Yoshiyuki Shibuya, and Pan Qin. "Synchronized tracking control of multiple Euler-Lagrange systems." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334722.

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Osunnuyi, Olufemi, Ognjen Marjanovic, Jian Wan, and Barry Lennox. "Trajectory tracking of exothermic batch reactor using NIR spectroscopy." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334771.

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Wu, Kang, and Wei Sun. "Adaptive tracking control for a new mobile manipulator model." In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915122.

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Dughman, S. S., and J. A. Rossiter. "Efficient robust feed forward model predictive control with tracking." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737593.

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Krok, Michael J. "Multi-target acquisition fire control simulation." In Acquisition, Tracking, and POinting IV. SPIE, 1990. http://dx.doi.org/10.1117/12.2322209.

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Wu, Caiyun, Georgi M. Dimirovski, and Jun Zhao. "Design of switching adaptive laws for the state tracking problem." In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334613.

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Araar, Oualid, and Nabil Aouf. "Quadrotor control for trajectory tracking in presence of wind disturbances." In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915110.

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Black, Bruce J. "Backlash control techniques in geared servo mechathcs." In Acquisition, Tracking, and POinting IV. SPIE, 1990. http://dx.doi.org/10.1117/12.2322195.

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Bigley, William J. "Supervisory control of EO tracking and pointing." In Acquisition, Tracking, and POinting IV. SPIE, 1990. http://dx.doi.org/10.1117/12.2322211.

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Reports on the topic "Tracking control"

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Verghese, George C., Benito Fernandez, and J. K. Hedrick. Stable, Robust Tracking by Sliding Mode Control,. Fort Belvoir, VA: Defense Technical Information Center, May 1987. http://dx.doi.org/10.21236/ada188278.

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Barrett, Steven F. Digital Tracking and Control of Retinal Images. Fort Belvoir, VA: Defense Technical Information Center, May 1993. http://dx.doi.org/10.21236/ada267490.

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Oates, William S., and Ralph C. Smith. Nonlinear Optimal Tracking Control of a Piezoelectric Nanopositioning Stage. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada443786.

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Beeler, S. C., H. T. Tran, and H. T. Banks. State Estimation and Tracking Control of Nonlinear Dynamical Systems. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada453162.

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Gibson, J. S. Adaptive Filtering and Estimation for Control and Target Tracking. Fort Belvoir, VA: Defense Technical Information Center, December 1999. http://dx.doi.org/10.21236/ada386878.

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Tannenbaum, Allen R. Distributed Systems for Problems in Robust Control and Visual Tracking. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada387787.

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Lee, DongBin, Timothy Burg, Bin Xian, and Darren Dawson. Output Feedback Tracking Control of an Underactuated Quad-Rotor UAV. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada462603.

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Moran, Shane C. An Adaptive H infinity Control Algorithm for Jitter Control and Target Tracking in a Directed Energy Weapon. Fort Belvoir, VA: Defense Technical Information Center, May 2012. http://dx.doi.org/10.21236/ada575864.

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Tannenbaum, Allen R. Geometric PDE's and Invariants for Problems in Visual Control Tracking and Optimization. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada428955.

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Dohner, J. L. A guidance and control algorithm for scent tracking micro-robotic vehicle swarms. Office of Scientific and Technical Information (OSTI), March 1998. http://dx.doi.org/10.2172/573345.

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