Relevant bibliographies by topics / Optimal control system

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Optimal control system'

Author: Grafiati
Published: 30 May 2022
Last updated: 10 March 2023

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Journal articles on the topic "Optimal control system"

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James, M. R. "Optimal Quantum Control Theory." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (May 3, 2021): 343–67. http://dx.doi.org/10.1146/annurev-control-061520-010444.

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This article explains some fundamental ideas concerning the optimal control of quantum systems through the study of a relatively simple two-level system coupled to optical fields. The model for this system includes both continuous and impulsive dynamics. Topics covered include open- and closed-loop control, impulsive control, open-loop optimal control, quantum filtering, and measurement feedback optimal control.
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Goncharenko, Borys, Larysa Vikhrova, and Mariia Miroshnichenko. "Optimal control of nonlinear stationary systems at infinite control time." Central Ukrainian Scientific Bulletin. Technical Sciences, no. 4(35) (2021): 88–93. http://dx.doi.org/10.32515/2664-262x.2021.4(35).88-93.

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The article presents a solution to the problem of control synthesis for dynamical systems described by linear differential equations that function in accordance with the integral-quadratic quality criterion under uncertainty. External perturbations, errors and initial conditions belong to a certain set of uncertainties. Therefore, the problem of finding the optimal control in the form of feedback on the output of the object is presented in the form of a minimum problem of optimal control under uncertainty. The problem of finding the optimal control and initial state, which maximizes the quality criterion, is considered in the framework of the optimization problem, which is solved by the method of Lagrange multipliers after the introduction of the auxiliary scalar function - Hamiltonian. The case of a stationary system on an infinite period of time is considered. The formulas that can be used for calculations are given for the first and second variations. It is proposed to solve the problem of control search in two stages: search of intermediate solution at fixed values of control and error vectors and subsequent search of final optimal control. The solution of -optimal control for infinite time taking into account the signal from the compensator output is also considered, as well as the solution of the corresponding matrix algebraic equations of Ricatti type.
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Shedrack Massawe, Estomih. "Optimal Control and Hamiltonian System." Pure and Applied Mathematics Journal 5, no. 3 (2016): 77. http://dx.doi.org/10.11648/j.pamj.20160503.13.

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Bulinskaya, E. V. "System stability and optimal control." Journal of Mathematical Sciences 92, no. 3 (November 1998): 3857–72. http://dx.doi.org/10.1007/bf02432356.

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Wada, Kenzo, Juniti Hamada, Hirohiko Nakamura, Hiroshi Ito, Atushi Miwa, and Eiji Morimoto. "Optimal Control of Grinding System." Transactions of the Japan Society of Mechanical Engineers Series C 59, no. 560 (1993): 1109–14. http://dx.doi.org/10.1299/kikaic.59.1109.

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Alt, Walter, Christopher Schneider, and Martin Seydenschwanz. "Optimal Control of an Optical System for Material Testing." IFAC-PapersOnLine 51, no. 2 (2018): 278–83. http://dx.doi.org/10.1016/j.ifacol.2018.03.048.

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TAKAHAMA, Morio, Takasi KIMURA, Ei TOKUDA, and Masahiro OHNO. "Flight Control System Design Using H.INF. Optimal Control." Journal of the Japan Society for Aeronautical and Space Sciences 41, no. 473 (1993): 324–29. http://dx.doi.org/10.2322/jjsass1969.41.324.

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Kalimoldayev, M., M. Jenaliyev, A. Abdildayeva, T. Zhukabayeva, and M. Akhmetzhanov. "OPTIMAL CONTROL OF POWER SYSTEMS." PHYSICO-MATHEMATICAL SERIES 5, no. 333 (October 15, 2020): 86–94. http://dx.doi.org/10.32014/2020.2518-1726.86.

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This article discusses the study of problems of optimal control for electric power systems. The numerical solution of optimal control problems for complex electric power systems using an iterative algorithm is shown. Also considered are issues of solving the optimal control of a nonlinear system of ordinary differential equations in two different cases. The proposed solution methods follow the principle of continuation of extremal problems based on sufficient conditions for optimality of V. F. Krotov. A special case of optimal control problems is considered. Numerical experiments showed sufficient efficiency of the implemented algorithms. The problem of optimal motion control of a two-system electric power system is graphically illustrated in the proposed numerical example.
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Chertovskoy, V., and V. Tsehanovsky. "Optimal model of manufacturing control system." Journal of Physics: Conference Series 1864, no. 1 (May 1, 2021): 012096. http://dx.doi.org/10.1088/1742-6596/1864/1/012096.

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Choi, Jeongju. "Optimal Control System of Traverse Grinding." Journal of the Korea Academia-Industrial cooperation Society 13, no. 12 (December 31, 2012): 5704–8. http://dx.doi.org/10.5762/kais.2012.13.12.5704.

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Dissertations / Theses on the topic "Optimal control system"

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Ding, Xu Chu. "Real-time optimal control of autonomous switched systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31725.

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Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2010.
Committee Chair: Egerstedt, Magnus; Committee Co-Chair: Wardi, Yorai; Committee Member: Riley, George; Committee Member: Taylor, David; Committee Member: Tovey, Craig; Committee Member: Yezzi, Anthony. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Hornung, Thomas. "Optimal control with ultrashort laser pulses." Diss., lmu, 2002. http://nbn-resolving.de/urn:nbn:de:bvb:19-2963.

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Hunt, K. J. "Stochastic optimal control theory with application in self-tuning control." Thesis, University of Strathclyde, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382399.

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Tsai, Mi-Ching. "Super-optimal control system design for multivariable plants." Thesis, University of Oxford, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238170.

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Barth, Eric J. "Approximating infinite horizon discrete-time optimal control using CMAC networks." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/19464.

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Liu, Ying. "An integrated optimal control system for emergency evacuation." College Park, Md. : University of Maryland, 2007. http://hdl.handle.net/1903/7018.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2007.
Thesis research directed by: Civil Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Hemasilpin, Nat. "Toward Optimal Adaptive Control of Hemodialysis." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378112378.

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Wang, Kon-King. "Complete synthesis of optimal control (single input linear systems)." Case Western Reserve University School of Graduate Studies / OhioLINK, 1993. http://rave.ohiolink.edu/etdc/view?acc_num=case1057165454.

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de, Azevedo Ricardo. "Fully Decentralized Multi-Agent System for Optimal Microgrid Control." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2461.

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In preparation for the influx of renewable energy sources that will be added to the electrical system, flexible and adaptable control schemes are necessary to accommodate the changing infrastructure. Microgrids have been gaining much attention as the main solution to the challenges of distributed and intermittent generation, but due to their low inertia, they need fast-acting control systems in order to maintain stability. Multi-Agent Systems have been proposed as dynamic control and communication frameworks. Decentralized arrangements of agents can provide resiliency and the much-desired “plug and play” behavior. This thesis describes a control system that implements droop control and the diffusion communication scheme without the need of a centralized controller to coordinate the Microgrid agents to maintain the frequency and stable operating conditions of the system. Moreover, the inter-agent communication is unaffected by changing network configurations and can achieve optimal economic dispatch through distributed optimization.
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Manzano, Ramos Edgar André. "Optimal control algorithm design for a prototype of active noise control system." Master's thesis, Pontificia Universidad Católica del Perú, 2017. http://tesis.pucp.edu.pe/repositorio/handle/123456789/8499.

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High-level noise can represent a serious risk for the health, industrial operations often represent continuous exposure to noise, thus an important trouble to handle. An alternative of solution can be the use of passive mechanisms of noise reductions, nonetheless its application cannot diminish low-frequency noise. Active Noise Control (ANC) is the solution used for low-frequency noise, ANC systems work according to the superposition principle generating a secondary anti-noise signal to reduce both. Nevertheless, the generation of an anti-noise signal with same oppose characteristics of the original noise signal presupposes the utilization of special techniques such as adaptive algorithms. These algorithms involve computational costs. The present research present the optimization of a specific ANC algorithm in the step-size criteria. Delayed Filtered-x LMS (FxLMS) algorithm using an optimal step-size is evaluated in a prototype of ANC system.
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Books on the topic "Optimal control system"

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Optimal control. New York: Springer, 2010.

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1922-, Markus L., ed. Foundations of optimal control theory. Malabar, Fla: R.E. Krieger Pub. Co., 1986.

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Chen, Chi-Tsong. Control system design: Conventional, algebraic, and optimal methods. Stony Brook, NY: Pond Woods Press, 1987.

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Patan, Maciej. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Hejmo, Władysław. Singular phenomena in a time-optimal feedback system. Kraków: Politechnika Krakowska im. Tadeusza Kościuszki, 1997.

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Singh, Tarunraj. Optimal reference shaping for dynamical systems: Theory and applications. Boca Raton: CRC Press, 2010.

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Uciński, Dariusz. Optimal measurement methods for distributed parameter system identification. Boca Raton, Fla: CRC Press, 2005.

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E, Helfrich Clifford, and United States. National Aeronautics and Space Administration., eds. Robust neighboring optimal guidance for the advanced launch system. [Austin, Tex.]: Guidance and Control Group, Dept. of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, 1993.

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1952-, Kunisch K. (Karl), and SpringerLink (Online service), eds. Optimal control of coupled systems of partial differential equations. Basel, Switzerland: Birkhäuser Verlag, 2009.

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Optimal measurement methods for distributed parameter system identification. Boca Raton, Fla: CRC Press, 2005.

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Book chapters on the topic "Optimal control system"

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Aschepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "Synthesis of the Optimal System Performance." In Optimal Control, 77–90. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49781-5_6.

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Ashchepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "Synthesis of the Optimal System Performance." In Optimal Control, 77–90. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91029-7_6.

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Bourdache-Siguerdidjane, Houria. "Stability Conditions in Terms of Eigenvalues of a Nonlinear Optimal Controlled System." In Optimal Control, 187–94. Basel: Birkhäuser Basel, 1993. http://dx.doi.org/10.1007/978-3-0348-7539-4_14.

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Tsui, Chia-Chi. "Control Design for LQ Optimal Control." In Robust Control System Design, 223–35. 3rd ed. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003259572-10.

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Claude, D., and N. Nadjar. "Nonlinear Control under Constraints of a Biological System." In Computational Optimal Control, 291–301. Basel: Birkhäuser Basel, 1994. http://dx.doi.org/10.1007/978-3-0348-8497-6_23.

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Ardema, Mark D., and Han-Chang Chou. "Second Order Algorithm for Time Optimal Control of a Linear System." In Computational Optimal Control, 117–26. Basel: Birkhäuser Basel, 1994. http://dx.doi.org/10.1007/978-3-0348-8497-6_10.

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Ericsson, Goran, Patrik Forsgren, and Erik Gyllensward. "An Object-Oriented Approach to Optimally Describe and Specify a SCADA System." In Computational Optimal Control, 303–18. Basel: Birkhäuser Basel, 1994. http://dx.doi.org/10.1007/978-3-0348-8497-6_24.

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Redfern, D. A., and C. J. Goh. "Feedback control of state constrained optimal control problems." In System Modelling and Optimization, 442–49. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-0-387-34897-1_53.

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Basu, Dipak, and Victoria Miroshnik. "Energy System Modeling." In Dynamic Systems Modeling and Optimal Control, 66–107. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137508959_4.

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Baev, Konstantin V. "The Spinal Motor Optimal Control System." In Biological Neural Networks: Hierarchical Concept of Brain Function, 87–101. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-4100-3_5.

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Conference papers on the topic "Optimal control system"

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Song, Sipeng, James F. Whidborne, Mudassir Lone, and Arturo Molina-Cristobal. "Multi-Objective Optimal Longitudinal Flight Control System Design for Large Flexible Transport Aircraft." In 2018 UKACC 12th International Conference on Control (CONTROL). IEEE, 2018. http://dx.doi.org/10.1109/control.2018.8516783.

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Belov, Mikhail, and Dmitry Novikov. "Optimal Enterprise: Engineering and Control." In 2020 IEEE 15th International Conference of System of Systems Engineering (SoSE). IEEE, 2020. http://dx.doi.org/10.1109/sose50414.2020.9130549.

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Cherng, Tzyh-Chyang, and Yoram Koren. "Stability of the Optimal Locus System." In 1989 American Control Conference. IEEE, 1989. http://dx.doi.org/10.23919/acc.1989.4790169.

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Wang, Zhi-Wen, and Hong-Hong Gao. "Linear quadratic optimal control of networked control system." In 2015 27th Chinese Control and Decision Conference (CCDC). IEEE, 2015. http://dx.doi.org/10.1109/ccdc.2015.7162282.

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Chikhi, F., and J. C. Cadiou. "Optimal Control for Anti-Braking System." In 2005 IEEE International Symposium on Intelligent Control and 13th Mediterranean Conference on Control and Automation. IEEE, 2005. http://dx.doi.org/10.1109/.2005.1467079.

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Selamat, Hazlina, Ahmad Jais Alimin, and Mohd Anwar Zawawi. "Optimal control of railway vehicle system." In 2009 IEEE International Conference on Industrial Technology - (ICIT). IEEE, 2009. http://dx.doi.org/10.1109/icit.2009.4939493.

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"Time optimal pneumatic valve control system." In Proceedings of the 1999 American Control Conference. IEEE, 1999. http://dx.doi.org/10.1109/acc.1999.782774.

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Shuai, Dong, Liu Lei, Ou Liuli, and Wang Yongji. "Optimal control of multi-missile system." In 2015 34th Chinese Control Conference (CCC). IEEE, 2015. http://dx.doi.org/10.1109/chicc.2015.7260727.

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Bigley, William J., and Steven P. Tsao. "Optimal Motion Stabilization Control Of An Electro-Optical Sight System." In SPIE 1989 Technical Symposium on Aerospace Sensing, edited by Sankaran Gowrinathan. SPIE, 1989. http://dx.doi.org/10.1117/12.977974.

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Yuzhen Xue and Martha A. Grover. "Optimal design for active self-assembly system." In 2011 American Control Conference. IEEE, 2011. http://dx.doi.org/10.1109/acc.2011.5990640.

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Reports on the topic "Optimal control system"

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Seginer, Ido, James Jones, Per-Olof Gutman, and Eduardo Vallejos. Optimal Environmental Control for Indeterminate Greenhouse Crops. United States Department of Agriculture, August 1997. http://dx.doi.org/10.32747/1997.7613034.bard.

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Increased world competition, as well as increased concern for the environment, drive all manufacturing systems, including greenhouses, towards high-precision operation. Optimal control is an important tool to achieve this goal, since it finds the best compromise between conflicting demands, such as higher profits and environmental concerns. The report, which is a collection of papers, each with its own abstract, outlines an approach for optimal, model-based control of the greenhouse environment. A reliable crop model is essential for this approach and a significant portion of the effort went in this direction, resulting in a radically new version of the tomato model TOMGRO, which can be used as a prototype model for other greenhouse crops. Truly optimal control of a very complex system requires prohibitively large computer resources. Two routes to model simplification have, therefore, been tried: Model reduction (to fewer state variables) and simplified decision making. Crop model reduction from nearly 70 state variables to about 5, was accomplished by either selecting a subset of the original variables or by forming combinations of them. Model dynamics were then fitted either with mechanistic relationships or with neural networks. To simplify the decision making process, the number of costate variables (control policy parametrs) was recuced to one or two. The dry-matter state variable was transformed in such a way that its costate became essentially constant throughout the season. A quasi-steady-state control algorithm was implemented in an experimental greenhouse. A constant value for the dry-matter costate was able to control simultaneously ventilation and CO2 enrichment by continuously producing weather-dependent optimal setpoints and then maintaining them closely.
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Kularatne, Dhanushka N., Subhrajit Bhattacharya, and M. Ani Hsieh. Computing Energy Optimal Paths in Time-Varying Flows. Drexel University, 2016. http://dx.doi.org/10.17918/d8b66v.

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Autonomous marine vehicles (AMVs) are typically deployed for long periods of time in the ocean to monitor different physical, chemical, and biological processes. Given their limited energy budgets, it makes sense to consider motion plans that leverage the dynamics of the surrounding flow field so as to minimize energy usage for these vehicles. In this paper, we present two graph search based methods to compute energy optimal paths for AMVs in two-dimensional (2-D) time-varying flows. The novelty of the proposed algorithms lies in a unique discrete graph representation of the 3-D configuration space spanned by the spatio-temporal coordinates. This enables a more efficient traversal through the search space, as opposed to a full search of the spatio-temporal configuration space. Furthermore, the proposed strategy results in solutions that are closer to the global optimal when compared to greedy searches through the spatial coordinates alone. We demonstrate the proposed algorithms by computing optimal energy paths around the Channel Islands in the Santa Barbara bay using time-varying flow field forecasts generated by the Regional Ocean Model System. We verify the accuracy of the computed paths by comparing them with paths computed via an optimal control formulation.
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Morkun, Volodymyr, Natalia Morkun, Andrii Pikilnyak, Serhii Semerikov, Oleksandra Serdiuk, and Irina Gaponenko. The Cyber-Physical System for Increasing the Efficiency of the Iron Ore Desliming Process. CEUR Workshop Proceedings, April 2021. http://dx.doi.org/10.31812/123456789/4373.

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It is proposed to carry out the spatial effect of high-energy ultrasound dynamic effects with controlled characteristics on the solid phase particles of the ore pulp in the deslimer input product to increase the efficiency of thickening and desliming processes of iron ore beneficiation products. The above allows predicting the characteristics of particle gravitational sedimentation based on an assessment of the spatial dynamics of pulp solid- phase particles under the controlled action of high-energy ultrasound and fuzzy logical inference. The object of study is the assessment of the characteristics and the process of control the operations of thickening and deslaming of iron ore beneficiation products in the conditions of the technological line of the ore beneficiation plant. The subject of study is a cyber-physical system based on the use of high-energy ultrasound radiation pressure effects on iron-containing beneficiation products in the technological processes of thickening and desliming. The working hypothesis of the project is that there is a relationship between the physical-mechanical and chemical-mineralogical characteristics of the iron ore pulp solid- phase particles and their behavior in technological flows under the influence of controlled ultrasonic radiation, based on which the imitation modeling of the gravitational sedimentation process of the iron ore pulp solid-phase particles can be performed directly in the technological process. Also, the optimal control actions concerning the processes of thickening and desliming can be determined.
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Duncan, Tyrone E., and Bozenna Pasik-Duncan. Optimal And Adaptive Control of Stochastic Systems. Fort Belvoir, VA: Defense Technical Information Center, February 2012. http://dx.doi.org/10.21236/ada567576.

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Gaponenko, Artiom, and Andrey Golovin. Electronic magazine with rating system of an estimation of individual and collective work of students. Science and Innovation Center Publishing House, October 2017. http://dx.doi.org/10.12731/er0043.06102017.

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«The electronic magazine with rating system of an estimation of individual and collective work of students» (EM) is developed in document Microsoft Excel with use of macros. EM allows to automate all the calculated operations connected with estimation of amount scored by students in each form of the current control. EM provides automatic calculation of rating of the student with reflection of a maximum quantity of the points received in given educational group. The rating equal to “1” is assigned to the student who has got a maximum quantity of points for the certain date. For the other students the share of their points in this maximum size is indicated. The choice of an estimation is made in an alphabetic format according to requirements of the European translation system of test units for the international recognition of results of educational outcomes (ECTS - European Credit Transfer System), by use of a corresponding scale of an estimation. The list of students is placed on the first page of magazine and automatically displayed on all subsequent pages. For each page of magazine the optimal size of document printing is set with automatic enter of current date and time. Owing to accounting rate of complexity of task EM is the universal technical tool which can be used for any subject matter.
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Gibson, J. S. Digital Adaptive and Optimal Control of Distributed Systems. Fort Belvoir, VA: Defense Technical Information Center, December 1993. http://dx.doi.org/10.21236/ada285352.

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Seidman, Thomas I. Optimal Design and Control of Distributed Parameter Systems. Fort Belvoir, VA: Defense Technical Information Center, September 1991. http://dx.doi.org/10.21236/ada254947.

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Lagutin, Andrey, and Tatyana Sidorina. SYSTEM OF FORMATION OF PROFESSIONAL AND PERSONAL SELF-GOVERNMENT AMONG CADETS OF MILITARY INSTITUTES. Science and Innovation Center Publishing House, December 2020. http://dx.doi.org/10.12731/self-government.

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When carrying out professional activities, officers of the VNG of the Russian Federation are often in difficult, stressful, emotionally stressful situations associated with the use of weapons as a particularly dangerous means of destruction. The right to use a weapon by an officer makes him responsible for its use. And therefore requires the officer to make a balanced optimal decision, which is associated with the risk and transience of events, and in which no mistake can be made, since the price of it can be someone's life. It is at such a moment that it is important that the officer has stable skills in making a decision on the use of weapons, and this requires skills not only in managing subordinates or the situation,but in managing himself. The complication of the military-professional activity, manifested in the need to develop the ability to quickly and accurately make command decisions, exacerbating the problem of social responsibility of an officer who has the management of unit that leads to an understanding of his singular personal and professional responsibility, as the ability to govern themselves makes it possible to achieve a positive result of the Department for the DBA. This characterizes the need for a commander to have the ability to manage himself, as a "system" that manages others. Forming skills of self-control, patience, compassion, having mastered algorithms of making managerial decisions, the cycle of implementing managerial functions, etc., a person comes to the belief: "before effectively managing others, it is necessary to learn how to manage yourself." The required level of personal and professional maturity can be formed in a person as a result of purposeful self-management, which determines the special role of professional and personal self-management in the training of future officers.
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Duncan, Tyrone E., and Bozenna Pasik-Duncan. Optimal Control of Stochastic Systems Driven by Fractional Brownian Motions. Fort Belvoir, VA: Defense Technical Information Center, October 2014. http://dx.doi.org/10.21236/ada614716.

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Kushner, Harold J., and R. M. Ramachandran. Nearly Optimal Singular Controls for Wideband Noise Driven Systems. Fort Belvoir, VA: Defense Technical Information Center, August 1986. http://dx.doi.org/10.21236/ada186682.

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