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Journal articles on the topic 'Optimal control system'

Author: Grafiati

Published: 30 May 2022

Last updated: 10 March 2023

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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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11

Nakashima *, K., H. Arimitsu, T. Nose, and S. Kuriyama. "Optimal control of a remanufacturing system." International Journal of Production Research 42, no. 17 (September 2004): 3619–25. http://dx.doi.org/10.1080/00207840410001721772.

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12

Asenjo, F., B. A. Toledo, V. Muñoz, J. Rogan, and J. A. Valdivia. "Optimal control in a noisy system." Chaos: An Interdisciplinary Journal of Nonlinear Science 18, no. 3 (September 2008): 033106. http://dx.doi.org/10.1063/1.2956981.

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13

Fister, K. Renee, and C. Maeve McCarthy. "Optimal control of a chemotaxis system." Quarterly of Applied Mathematics 61, no. 2 (June 1, 2003): 193–211. http://dx.doi.org/10.1090/qam/1976365.

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14

Li, Guo-Dong, Shiro Masuda, Daisuke Yamaguchi, and Masatake Nagai. "An Optimal Grey PID Control System." IEEJ Transactions on Electrical and Electronic Engineering 4, no. 4 (July 2009): 570–77. http://dx.doi.org/10.1002/tee.20445.

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15

Oliynyk, Viktor, Fedir Zhuravka, Tetiana Bolgar, and Olha Yevtushenko. "Optimal control of continuous life insurance model." Investment Management and Financial Innovations 14, no. 4 (December 8, 2017): 21–29. http://dx.doi.org/10.21511/imfi.14(4).2017.03.

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The problems of mixed life insurance and insurance in the case of death are considered in the article. The actuarial present value of life insurance is found by solving a system of differential equations. The cases of both constant effective interest rates and variables, depending on the time interval, are examined. The authors used the Pontryagin maximum principle method as the most efficient one, in order to solve the problem of optimal control of the mixed life insurance value. The variable effective interest rate is considered as the control parameter. Some numerical results were given.

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16

Pan, Shing, and Fuliang Yin. "Optimal Control of Chaos with Synchronization." International Journal of Bifurcation and Chaos 07, no. 12 (December 1997): 2855–60. http://dx.doi.org/10.1142/s021812749700193x.

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Optimal control of chaotic systems is discussed in this paper. Since often only open-loop control can be obtained from the minimum principle, the output of the controlled system may be dramatically affected by noise. By using chaos synchronization, we successfully keep the output of the controlled chaotic system in the designed optimal trajectory even in noisy background. The numerical experiments of the Rössler system and the Hénon system are presented to demonstrate its effectiveness.

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17

Zhang, Lijie, Wenbo Fu, Xiaoming Yuan, and Zhaoliang Meng. "Research on Optimal Control of Excavator Negative Control Swing System." Processes 8, no. 9 (September 4, 2020): 1096. http://dx.doi.org/10.3390/pr8091096.

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In order to improve the energy efficiency and dynamic of negative control swing systems of excavators, this paper proposes a technical scheme of adding two PRVs (pressure reducing valves) to main valve pilot control circuit, which can adjust main value opening arbitrarily according to the working condition. A pump-value compound control strategy was formulated to regulate the system power flow. During swing motor acceleration, main pump and the two PRVs are controlled to match system supply flow with motor demand flow, thereby reducing motor overflow and shortening system response time. During swing motor braking, the channel from motor to tank is opened to release hydraulic brake pressure by controlling PRVs before swing speed reduces to zero, which prevents the motor from reversing and oscillating. A simulation model of 37-ton excavator was established, and the control strategy was simulated. The original and optimized performance of the swing system were compared and analyzed, and results show that the application of new scheme with the compound control strategy can reduce overflow and increase braking stability of the swing system. In addition, system response and speed control performance are also improved when excavator performs a single-swing action.

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18

Nwokah, Osita D. I., E. Borzova, Gemunu S. Happawana, and Dare´ Afolabi. "Catastrophes in Optimal Control." Journal of Dynamic Systems, Measurement, and Control 121, no. 4 (December 1, 1999): 577–82. http://dx.doi.org/10.1115/1.2802518.

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System optimization over a parameter space produces optimal solutions which lie on the bifurcation set of the ambient space. As such, the optimality (quality) metric (as a function of the parameters) is highly sensitive to the parameters, to the point of inducing instability for differential parameter variations. Singularities in this function diffeomorphically induce corresponding degenerate singularities in the optimal closed-loop characteristic polynomials, which serves as a signature for potential catastrophic loss of quality that is most easily exhibited by the resulting dynamic instability. In this paper, we examine the loss of quality in H∞ and related optimal systems via these diffeomorphic degenerate closed-loop poles.

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19

Liu, Qiyu, Qunxiong Zhu, Zhiqiang Geng, and Longjin Lv. "Time Optimal Control of a Thermoelastic System." Mathematical Problems in Engineering 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/6047670.

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This paper considers the numerical approximation for the time optimal control problem of a thermoelastic system with some control and state constraints. By the Galerkin finite element method (FEM), the original problem is projected into a semidiscrete optimal control problem governed by a system of ordinary differential equations. Then the optimal time and control parameterization method is applied to reduce the original system to an optimal parameter selection problem, in which both the optimal time and control are taken as decision variables to be optimized. This problem can be solved as a nonlinear optimization problem by a hybrid algorithm consisting of chaotic particle swarm optimization (CPSO) and sequential quadratic programming (SQP) algorithm. The numerical simulations demonstrate the effectiveness of the proposed numerical approximation method.

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20

KAWAMURA, Hitoshi, and Takeshi TSUCHIYA. "Asymptotic Characteristics of Optimal Preview Control System." Transactions of the Society of Instrument and Control Engineers 25, no. 10 (1989): 1083–90. http://dx.doi.org/10.9746/sicetr1965.25.1083.

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21

Farkh, Rihem, Moufida Ksouri, and Faouzi Bouani. "Optimal Robust Control for Unstable Delay System." Computer Systems Science and Engineering 36, no. 2 (2021): 307–21. http://dx.doi.org/10.32604/csse.2021.014334.

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22

Suebsomran, Anan. "Optimal Control of Electromagnetic Suspension EMS System." Open Automation and Control Systems Journal 6, no. 1 (March 7, 2014): 1–8. http://dx.doi.org/10.2174/1874444301406010001.

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23

Noda, Kengo, Kazuyoshi Miyata, Yasuhiro Nakano, and Hiroshi Murata. "Disturbance Characteristics of Optimal Deadbeat Control System." IEEJ Transactions on Electronics, Information and Systems 118, no. 4 (1998): 528–35. http://dx.doi.org/10.1541/ieejeiss1987.118.4_528.

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24

Tang, Xin Tong, and Chang Qing Cai. "Optimal Control of the Industrial Furnace System." Advanced Materials Research 383-390 (November 2011): 3077–80. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.3077.

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Control system of industrial furnace is optimized based on the aspect of the combustion. General goal of the control system is to achieve the lowest fuel with the constraints of ensuring the target control temperature of the equipment. And in different output and different fuel quantity conditions, the air-fuel rate is automatically optimized to achieve the goal of energy consumption combined with gas temperature of furnace temperature, oxygen and many parameters.

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25

Zubov, D. V., E. A. Paramonov, and A. A. Tolchenov. "System of optimal control the cellulases biosynthesis." Izvestiya MGTU MAMI 6, no. 2-4 (December 20, 2012): 324–26. http://dx.doi.org/10.17816/2074-0530-68504.

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The production of enzymes from the waste of food production is of great ecological importance, but there are some difficulties connected with the instability of the raw materials used and the difficulty of operational control of the fermentation process. The paper proposes to use periodically updated mathematical biosynthesis model of the enzyme to determine the best moment of the process cessation.

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26

Naganawa, Akihiro, Eri Kobayashi, Kazuo Aida, and Goro Obinata. "Design of Optimal Generalized Predictive Control System." IEEJ Transactions on Industry Applications 119, no. 10 (1999): 1252–58. http://dx.doi.org/10.1541/ieejias.119.1252.

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27

Schuler, Simone, Christian Ebenbauer, and Frank Allgöwer. "ℓ0-System Gain and ℓ1-Optimal Control." IFAC Proceedings Volumes 44, no. 1 (January 2011): 9230–35. http://dx.doi.org/10.3182/20110828-6-it-1002.00755.

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28

Szarkowicz, Donald S., and Thomas W. Knowles. "Optimal Control of anM/M/SQueueing System." Operations Research 33, no. 3 (June 1985): 644–60. http://dx.doi.org/10.1287/opre.33.3.644.

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29

Wang, Wencan. "Optimal control of backward doubly stochastic system." IET Control Theory & Applications 13, no. 12 (August 13, 2019): 1844–54. http://dx.doi.org/10.1049/iet-cta.2018.6249.

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30

Sun, Yun, and Yuanguo Zhu. "Optimal Control of a Multifactor Uncertain System." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 27, no. 03 (May 29, 2019): 397–414. http://dx.doi.org/10.1142/s0218488519500181.

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Along with the development of the modern science and technology, people face a lot of data in different areas of production and life. In dealing with these data which include many indeterminant factors, we can use the multifactor uncertain system to describe a dynamical system with uncertain noises. Optimal control problem is an important research topic which aims at finding the optimal strategy in a dynamical system. In this paper, we consider the optimal control problem for the multifactor uncertain system with two evaluation criterions. Then a two person zero sum differential game model in a multifactor uncertain system is discussed. Finally, as an application, our result is used to solve an uncertain portfolio game model.

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31

Rivera, P. H., and C. F. Vasconcellos. "Optimal Control for a Backward Parabolic System." SIAM Journal on Control and Optimization 25, no. 5 (September 1987): 1163–72. http://dx.doi.org/10.1137/0325063.

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32

Larsen, Mads B., Torben F. H. Kristensen, and Hans Holm. "Automated Optimal Closed Loop Control System Design." IFAC Proceedings Volumes 33, no. 17 (July 2000): 753–58. http://dx.doi.org/10.1016/s1474-6670(17)39497-1.

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33

Alexandrov, V. M. "Optimal Control of a System Under Disturbance." IFAC Proceedings Volumes 31, no. 13 (June 1998): 53–58. http://dx.doi.org/10.1016/s1474-6670(17)35995-5.

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34

Chen, Hong, Ping Yang, David D. Yao, and Xiuli Chao. "Optimal control of a simple assembly system." Operations Research Letters 14, no. 4 (November 1993): 199–205. http://dx.doi.org/10.1016/0167-6377(93)90070-w.

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35

Burger, J., and J. Taoud. "Optimal Control of a Non-Linear System." IFAC Proceedings Volumes 22, no. 4 (June 1989): 141–45. http://dx.doi.org/10.1016/s1474-6670(17)53533-8.

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36

El Bagdouri, M. "Optimal Control of a Nonlinear Thermal System." IFAC Proceedings Volumes 22, no. 4 (June 1989): 153–58. http://dx.doi.org/10.1016/s1474-6670(17)53535-1.

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37

Qing Zhang, G. G. Yin, and E. K. Boukas. "Optimal control of a marketing-production system." IEEE Transactions on Automatic Control 46, no. 3 (March 2001): 416–27. http://dx.doi.org/10.1109/9.911418.

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38

Kalboussi, N., A. Rapaport, T. Bayen, N. Ben Amar, F. Ellouze, and J. Harmand. "Optimal control of a membrane filtration system." IFAC-PapersOnLine 50, no. 1 (July 2017): 8704–9. http://dx.doi.org/10.1016/j.ifacol.2017.08.1554.

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39

Reid, D. W., and K. L. Teo. "Optimal control problems with fuzzy system parameters." Mathematical and Computer Modelling 16, no. 3 (March 1992): 3–13. http://dx.doi.org/10.1016/0895-7177(92)90042-j.

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40

Vlasenko, L. A., A. G. Rutkas, V. V. Semenets, and A. A. Chikrii. "Stochastic Optimal Control of a Descriptor System." Cybernetics and Systems Analysis 56, no. 2 (March 2020): 204–12. http://dx.doi.org/10.1007/s10559-020-00236-7.

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41

HASSAN, S., E. EL-MEHEIRY, and S. EL-SHAKERY. "OPTIMAL MODIFIED COMBINED SYSTEM FOR VIBRATION CONTROL." International Conference on Aerospace Sciences and Aviation Technology 4, ASAT CONFERENCE (May 1, 1991): 1–17. http://dx.doi.org/10.21608/asat.1991.25761.

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42

Gashimov, S. "Optimal control in quasilinear loaded parabolic system." Актуальные направления научных исследований XXI века: теория и практика 2, no. 4 (October 10, 2014): 292–95. http://dx.doi.org/10.12737/4762.

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43

Toleukhan, Imankul. "Optimal Control of the Rotor System Motion." Advanced Materials Research 705 (June 2013): 546–52. http://dx.doi.org/10.4028/www.scientific.net/amr.705.546.

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Among the problems of the rotor machines dynamics the special attention is given to the problems of creation of the automatic balancing devices (ABD) in form of a hollow rotor, filled by a liquid, and the liquid-solidbody ABD. The theoretical and experimental works on research of the ABD on the base of a hollow rotor filled partially with a liquid and of the liquid-solidbody ABD are not enough. Therefore development of the methods of research of dynamics of the rotor machines with the ABD and such machines designs is an actual, new and perspective problem. In the present work the mathematical model of the rotor system with the ABD taking into account of the engine characteristics is offered. Lets consider the model of the rotor with electric drive with one disk, set up at the flexible shaft without skew. The shaft is lean on two bearings (fig. 1).

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44

Unami, Koichi, Susumu Kurata, Toshihiko Kawachi, and Kazuo Morishita. "Optimal Control of Interconnected Irrigation Tanks System." Journal of Rainwater Catchment Systems 8, no. 2 (2003): 35–39. http://dx.doi.org/10.7132/jrcsa.kj00000795203.

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45

Gabasov, R., F. M. Kirillova, and N. S. Pavlenok. "An optimal control of a hybrid system." Doklady Mathematics 76, no. 3 (December 2007): 976–82. http://dx.doi.org/10.1134/s1064562407060427.

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46

Melnyk, Matthew P., and Dong Eui Chang. "Time optimal control of a dielectrophoretic system." Asian Journal of Control 13, no. 4 (March 26, 2010): 480–91. http://dx.doi.org/10.1002/asjc.181.

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47

Razmara, M., M. Maasoumy, M. Shahbakhti, and R. D. Robinett. "Optimal exergy control of building HVAC system." Applied Energy 156 (October 2015): 555–65. http://dx.doi.org/10.1016/j.apenergy.2015.07.051.

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48

Sánchez Chávez, Irma Y., Rubén Morales-Menéndez, and Sergio O. Martínez Chapa. "Glucose optimal control system in diabetes treatment." Applied Mathematics and Computation 209, no. 1 (March 2009): 19–30. http://dx.doi.org/10.1016/j.amc.2008.06.030.

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49

Zheng, G. R., and M. Zaheer-Uddin. "Discharge air system: modelling and optimal control." International Journal of Energy Research 23, no. 8 (June 25, 1999): 727–38. http://dx.doi.org/10.1002/(sici)1099-114x(19990625)23:8<727::aid-er512>3.0.co;2-z.

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50

Sun, Eric D., Thomas C. T. Michaels, and L. Mahadevan. "Optimal control of aging in complex networks." Proceedings of the National Academy of Sciences 117, no. 34 (August 12, 2020): 20404–10. http://dx.doi.org/10.1073/pnas.2006375117.

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Many complex systems experience damage accumulation, which leads to aging, manifest as an increasing probability of system collapse with time. This naturally raises the question of how to maximize health and longevity in an aging system at minimal cost of maintenance and intervention. Here, we pose this question in the context of a simple interdependent network model of aging in complex systems and show that it exhibits cascading failures. We then use both optimal control theory and reinforcement learning alongside a combination of analysis and simulation to determine optimal maintenance protocols. These protocols may motivate the rational design of strategies for promoting longevity in aging complex systems with potential applications in therapeutic schedules and engineered system maintenance.

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