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Journal articles on the topic 'Optimal temperature control'

Author: Grafiati

Published: 25 May 2024

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1

Tian-Yu, Liu, Cao Jia-Hui, Liu Yan-Yan, Gao Tian-Fu, and Zheng Zhi-Gang. "Optimal control of temperature feedback control ratchets." Acta Physica Sinica 70, no. 19 (2021): 190501. http://dx.doi.org/10.7498/aps.70.20210517.

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2

Schwalbe, Karsten, and Karl Heinz Hoffmann. "Optimal Control of an Endoreversible Solar Power Plant." Journal of Non-Equilibrium Thermodynamics 43, no. 3 (July 26, 2018): 255–71. http://dx.doi.org/10.1515/jnet-2018-0021.

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AbstractWhile in the classic Curzon–Ahlborn and Novikov engines the temperatures of the heat baths are kept fixed or follow a deterministic time function, it is the aim of this work to study the impact of fluctuating heat bath temperatures. As an example serves a solar power plant, where the stochastically varying cloud cover leads to fluctuations in the temperature of the hot heat bath. This solar thermal power plant is modeled as a stochastic endoreversible system. On the basis of this model the maximum expected work output of the power plant and the corresponding optimal control policy is derived. For the considered system it is found that the maximum expected work output changes with the reversion speed of the hot temperature depending on the relation of the starting hot temperature and the temperature of the power plant’s receiver. Additionally, it is found that the maximum expected work output increases with the hot temperature’s fluctuation strength.

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3

Agusto, Folashade B. "Optimal Control and Temperature Variations of Malaria Transmission Dynamics." Complexity 2020 (November 28, 2020): 1–32. http://dx.doi.org/10.1155/2020/5056432.

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Malaria is a Plasmodium parasitic disease transmitted by infected female Anopheles mosquitoes. Climatic factors, such as temperature, humidity, rainfall, and wind, have significant effects on the incidence of most vector-borne diseases, including malaria. The mosquito behavior, life cycle, and overall fitness are affected by these climatic factors. This paper presents the results obtained from investigating the optimal control strategies for malaria in the presence of temperature variation using a temperature-dependent malaria model. The study further identified the temperature ranges in four different geographical regions of sub-Saharan Africa, suitable for mosquitoes. The optimal control strategies in the temperature suitable ranges suggest, on average, a high usage of both larvicides and adulticides followed by a moderate usage of personal protection such as bednet. The average optimal bednet usage mimics the solution profile of the mosquitoes as the mosquitoes respond to changes in temperature. Following the results from the optimal control, this study also investigates using a temperature-dependent model with insecticide-sensitive and insecticide-resistant mosquitoes the impact of insecticide-resistant mosquitoes on disease burden when temperature varies. The results obtained indicate that optimal bednet usage on average is higher when insecticide-resistant mosquitoes are present. Besides, the average bednet usage increases as temperature increases to the optimal temperature suitable for mosquitoes, and it decreases after that, a pattern similar to earlier results involving insecticide-sensitive mosquitoes. Thus, personal protection, particularly the use of bednets, should be encouraged not only at low temperatures but particularly at high temperatures when individuals avoid the use of bednets. Furthermore, control and reduction of malaria may be possible even when mosquitoes develop resistance to insecticides.

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4

Kull, Tuule Mall, Martin Thalfeldt, and Jarek Kurnitski. "Optimal PI control parameters for accurate underfloor heating temperature control." E3S Web of Conferences 111 (2019): 01081. http://dx.doi.org/10.1051/e3sconf/201911101081.

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In low energy buildings, the effect of internal and solar gains on heat balance of rooms is large. As a result, the heating systems, designed assuming steady-state conditions with no heat gains, are over-dimensioned for most of the heating period. This poses a challenge for room-based control systems, especially for thermostatic valves, but also for PI controllers. Using over-dimensioned room units might result in room temperature fluctuations. For finding solutions to this problem by using simulations, correct modelling of the control system together with the room is crucial. Therefore, the aim of this research was to determine the challenges that occur while matching measured and simulated temperature profiles and test the effect of PI control parameters on the calibrated model control accuracy. The experiments were carried out for the underfloor heating system of a test building. The building was simulated in IDA-ICE software and calibration via minimising root mean square error of energy consumption in GenOpt was carried out. The PI parameters were fit by optimisation with objective to simulate the measured temperatures accurately. The effect of the optimized PI parameters was determined by comparison to IDA-ICE default parameters and parameters from Cohen-Coon method.

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5

Park, Young-shin, and Dongju Lee. "Optimal PID Control for Temperature Control of Chiller Equipment." Journal of Society of Korea Industrial and Systems Engineering 45, no. 3 (September 30, 2022): 131–38. http://dx.doi.org/10.11627/jksie.2022.45.3.131.

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6

Veldman, D. W. M., S. A. N. Nouwens, R. H. B. Fey, H. J. Zwart, M. M. J. van de Wal, J. D. B. J. van den Boom, and H. Nijmeijer. "Optimal thermal actuation for mirror temperature control." Computer Methods in Applied Mechanics and Engineering 398 (August 2022): 115212. http://dx.doi.org/10.1016/j.cma.2022.115212.

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7

Yang, Xing Hua, Ting Rui Liu, and Jing Sun. "Optimal PID Control of Heat Exchanger Temperature." Advanced Materials Research 204-210 (February 2011): 21–24. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.21.

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To maintain the outlet temperature at the desired set-point, a high-order outlet temperature control model is established for a shell-and–tube heat exchanger, which is based on the analysis of its heat transfer process and dynamic properties .The Optimal PID control is applied to the temerature control system on the basis of this model, and the tuning parameters of the PID controller are obtained by numerical solving of a formulated optimization problem using Matlab/Simulink. An experimental control system is set up to testify the effect of the optimal PID control. The simulation result and the practice show that the control system has a favorable control performance.

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8

Van Henten, E. J., and J. Bontsema. "OPEN-LOOP OPTIMAL TEMPERATURE CONTROL IN GREENHOUSES." Acta Horticulturae, no. 801 (November 2008): 629–36. http://dx.doi.org/10.17660/actahortic.2008.801.72.

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9

SHarshenaliev, J. SH, T. P. Samochvalova, and IU M. Leschenko. "Optimal control by temperature of stacks polysilicon." IFAC Proceedings Volumes 37, no. 17 (September 2004): 276–79. http://dx.doi.org/10.1016/s1474-6670(17)30827-3.

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10

Gee, Douglas A., and W. Fred Ramirez. "Optimal temperature control for batch beer fermentation." Biotechnology and Bioengineering 31, no. 3 (February 20, 1988): 224–34. http://dx.doi.org/10.1002/bit.260310308.

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11

Uysal, Mithat, and Murat Tunç. "Optimal temperature control of solar heating systems." International Journal of Energy Research 15, no. 4 (May 1991): 269–73. http://dx.doi.org/10.1002/er.4440150403.

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12

Tsirlin, A. M. "Methods of Simplifying Optimal Control Problems, Heat Exchange and Parametric Control of Oscillators." Nelineinaya Dinamika 18, no. 4 (2022): 0. http://dx.doi.org/10.20537/nd220801.

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Methods of simplifying optimal control problems by decreasing the dimension of the space of states are considered. For this purpose, transition to new phase coordinates or conversion of the phase coordinates to the class of controls is used. The problems of heat exchange and parametric control of oscillators are given as examples: braking/swinging of a pendulum by changing the length of suspension and variation of the energy of molecules’ oscillations in the crystal lattice by changing the state of the medium (exposure to laser radiation). The last problem corresponds to changes in the temperature of the crystal.

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13

Wong, K. H., and N. Lock. "Optimal control of a chemical reactor." Journal of the Australian Mathematical Society. Series B. Applied Mathematics 39, no. 1 (July 1997): 61–76. http://dx.doi.org/10.1017/s0334270000009218.

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AbstractA chemical reactor problem is considered governed by partial differential equations. We wish to control the input temperature and the input oxygen concentration so that the actual output temperature can be as close to the desired output temperature as possible. By linearizing the differential equations around a nominal equation and then applying a finite-element Galerkin Scheme to the resulting system, the original problem can be converted into a sequence of linearly-constrained quadratic programming problems.

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14

Zheng, Li Kun, Yan Zhou, and Dan Mei Xie. "Optimal Control of Turbine Thermal Fatigue Life." Advanced Materials Research 823 (October 2013): 236–40. http://dx.doi.org/10.4028/www.scientific.net/amr.823.236.

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As for turbine rotor, the simple stress on-line monitoring models of rotors temperature and thermal stress based on Greens function method are obtained. Using perturbation method, the models can deal with nonlinear problems resulting from temperature dependent properties. The working medium temperature change curve and the temperature rising rate curve during the period of startup or shutdown at shortest time for unit can be obtained to reduce fatigue wastage by analyzing the startup or shutdown process of a unit plant with the Pontryagin Maximum Principle of optimal control theory. The temperature rising rate curve thus obtained can be used not only as a guide for operation, but also as a programmable control signal for the startup and shutdown process of generating units, which will improve the economy of a power plant.

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15

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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16

Knudsen, M., and U. Hartmann. "Optimal Temperature Control with Phased Array Hyperthermia System." IEEE Transactions on Microwave Theory and Techniques 34, no. 5 (May 1986): 597–603. http://dx.doi.org/10.1109/tmtt.1986.1133398.

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17

Xue, Musen, Jianxiong Zhang, and Wansheng Tang. "Optimal temperature control for quality of perishable foods." ISA Transactions 53, no. 2 (March 2014): 542–46. http://dx.doi.org/10.1016/j.isatra.2013.12.011.

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18

Kawahara, Mutsuto, Ken-Ichi Sasaki, and Yasuhiko Sano. "Parameter identification and optimal control of ground temperature." International Journal for Numerical Methods in Fluids 20, no. 8-9 (April 30, 1995): 789–801. http://dx.doi.org/10.1002/fld.1650200807.

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19

Gee, Douglas A., and W. Fred Ramirez. "Optimal temperature control of jacket-cooled fermentation reactors." Optimal Control Applications and Methods 12, no. 1 (January 1991): 49–62. http://dx.doi.org/10.1002/oca.4660120105.

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20

Pervadchuk, Vladimir, Daria Vladimirova, Irina Gordeeva, Alex G. Kuchumov, and Dmitrij Dektyarev. "Fabrication of Silica Optical Fibers: Optimal Control Problem Solution." Fibers 9, no. 12 (November 29, 2021): 77. http://dx.doi.org/10.3390/fib9120077.

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In this work, a new approach to solving problems of optimal control of manufacture procedures for the production of silica optical fiber are proposed. The procedure of silica tubes alloying by the Modified Chemical Vapor Deposition (MCVD) method and optical fiber drawing from a preform are considered. The problems of optimal control are presented as problems of controlling distributed systems with objective functionals and controls of different types. Two problems are formulated and solved. The first of them is the problem of the temperature field optimizing in the silica tubes alloying process in controlling the consumption of the oxygen–hydrogen gas mixture (in the one- and two-dimensional statements), the second problem is the geometric optimization of fiber shape in controlling the drawing velocity of the finished fiber. In both problems, while using an analog to the method of Lagrange, the optimality systems in the form of differential problems in partial derivatives are obtained, as well as formulas for finding the optimal control functions in an explicit form. To acquire optimality systems, the qualities of lower semicontinuity, convexity, and objective functional coercivity are applied. The numerical realization of the obtained systems is conducted by using Comsol Multiphysics.

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21

Zhao, Zhen, Lei Xi, Jianmin Gao, Liang Xu, and Yunlong Li. "Numerical Study on the Heating Effect of a Spring-Loaded Actuator—Part II: Optimization Design of Heater Parameters." Actuators 12, no. 5 (May 21, 2023): 212. http://dx.doi.org/10.3390/act12050212.

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Unfavorable temperatures and humidity will cause the failure of spring actuators. In order to ensure the safe operation of the actuator, it is necessary to optimize the design of the built-in heater system of the actuator itself. In this study, an experimental design and a response surface model were used to fit the empirical formulas for the minimum temperature, maximum humidity, and maximum temperature on the heater surface. On this basis, a genetic algorithm was used to establish the optimal size of the heater in the chamber of the spring actuator. The study results show that the air inside the actuator shows a trend of a decrease in temperature and an increase in relative humidity from top to bottom. The empirical equation obtained by fitting the second-order response surface model has high accuracy, and the maximum prediction errors for the minimum temperature, maximum relative humidity, and maximum temperature of the heater surface of the spring actuator are −0.5%, 11.7%, and 4.7%, respectively. When the environmental temperature reduces from 313 K to 233 K, the optimal heating power of the heater increases from 10 W to 490 W, the optimal relative length increases from 3.57 to 6, and the optimal relative width increases from 1 to 5.3. Therefore, the study can act as a reference for the temperature and humidity control system of future actuators.

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22

TSE, OLIVER, RENÉ PINNAU, and NORBERT SIEDOW. "IDENTIFICATION OF TEMPERATURE-DEPENDENT PARAMETERS IN LASER-INTERSTITIAL THERMO THERAPY." Mathematical Models and Methods in Applied Sciences 22, no. 09 (July 31, 2012): 1250019. http://dx.doi.org/10.1142/s0218202512500194.

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Laser-induced thermotherapy (LITT) is an established minimally invasive percutaneous technique of tumor ablation. Nevertheless, there is a need to predict the effect of laser applications and optimize irradiation planning in LITT. Optical attributes (attenuation, absorption, scattering) change due to thermal denaturation. The work presents the possibility to identify these temperature-dependent parameters from given temperature measurements via an optimal control problem. The solvability of the optimal control problem is analyzed and results of successful implementations are shown.

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23

Hou, Juan, Haoran Li, and Natasa Nord. "Optimal control of secondary side supply water temperature for substation in district heating systems." E3S Web of Conferences 111 (2019): 06015. http://dx.doi.org/10.1051/e3sconf/201911106015.

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Low temperature is the most significant feature of the future district heating system- the 4th generation district heating (4GDH). However, a widely used control strategy for supply water temperature in substation is weather- compensated control. It is a feedforward control without any dynamic information about buildings, which can lead to higher or lower supply water temperature. This paper presents model predictive controller (MPC) applied to the supply water temperature control for substations in district heating systems. MPC is an advanced control technique, which can make full use of dynamic information of buildings to determine the optimal supply water temperature of substations. In this paper, a multiple inputs and single output dynamic model was identified by subspace methods. Two different MPC controllers were designed in Simulink. The MPC controller 1 focused on keeping indoor air temperature at reference values. The MPC controller 2 focused on both keeping indoor air temperature at reference values and tracking the minimum supply water temperature in order to find the temperature potential for the future DH systems. Both of the MPC controllers proved to have a better tracking effect for indoor air temperature and lower average supply temperatures compared to weather- compensated. The MPC controller 2 could further lower supply water temperature compared to the MPC controller 1 by tracking minimum supply water temperature in its objective function. The average supply water temperatures for the weather- compensated, the MPC controller1, and the MPC controller 2 were 52°C, 51°C and 50°C, respectively. The results showed that MPC has a great potential in the area of supply water temperature control of the district heating systems.

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24

Mallea-Zepeda, Exequiel, Eber Lenes, and Elvis Valero. "Boundary Control Problem for Heat Convection Equations with Slip Boundary Condition." Mathematical Problems in Engineering 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/7959761.

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We analyze an optimal boundary control problem for heat convection equations in a three-dimensional domain, with mixed boundary conditions. We prove the existence of optimal solutions, by considering boundary controls for the velocity vector and the temperature. The analyzed optimal control problem includes the minimization of a Lebesgue norm between the velocity and some desired field, as well as the temperature and some desired temperature. By using the Lagrange multipliers theorem we derive an optimality system. We also give a second-order sufficient condition.

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25

Popov, Anton Valerjevich, Anna Nikolayevna Diligenskaya, and Darya Aleksandrovna Vertyankina. "Parametric identification and induction heating process optimal control." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2023, no. 4 (November 9, 2023): 7–16. http://dx.doi.org/10.24143/2072-9502-2023-4-7-16.

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In the paper the experimental induction heating installation for through heating of steel cylindrical workpieces is considered. It is well known that the use of an industrial heating system presupposes incomplete information about its main characteristics due to the complex nature of changes in some parameters both from the ambient temperature and from the temperature of the heated part. These parameters primarily include the coefficients of convective and emissive heat transfer from the surface of the workpiece. At the first step, it is necessary to obtain the values of unknown parameters, which also include the voltage of the power source, and then solve the optimal control problem. The problem of identifying these parameters is solved using the alternance method of parametric optimization of systems with distributed parameters, using experimental data from thermocouples. The obtained values of unknown parameters are then used in a numerical finite-element FLUX model of the considered process. Based on the developed model, the problem of time-optimal control with an additional phase restriction on the maximum temperature is formulated. This problem is solved using the alternance method. The solution of the problem made it possible to obtain a emperature field with a maximum deviation of 32 °C from the required temperature T* = 1 200 °C. This value is less than 3% of the desired temperature value and fully meets the technological requirements for induction through heating processes prior subsequent plastic deformation. The maximum temperature in this case does not exceed the maximum permissible value of 1 300 °C during the entire heating process.

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26

Astashova, I. V., D. A. Lashin, and A. V. Filinovskiy. "ON A MODEL OF OPTIMAL TEMPERATURE CONTROL IN HOTHOUSES." Vestnik of Samara University. Natural Science Series 22, no. 3-4 (April 14, 2017): 14–23. http://dx.doi.org/10.18287/2541-7525-2016-22-3-4-14-23.

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While growing plants in industrial hothouses it needs to keep the temperature according to round-the-clock graph at the point of growth of plant located at the fixed height. Only small deviations are admitted. To obtain this it is possible to increase the temperature by heating the floor and to decrease the temperature by opening the ventilator windows at the ceiling. We propose and analyse the model based on the heat equation. Physical sense of this problem is that at one end of the infinitely thin rod of length l (the height of the hothouse) we keep during the time T the temperature ϕ(t) (control function), while at the other end we have the given heat flow ψ(t). It requires to find the control function ϕ0(t) such that the temperature at the fixed point c be maximally closed to the given temperature z(t). For the estimation of the control quality we use a quadratic integral functional.

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27

Engelbrecht, J. A. A., M. J. Ritchie, and M. J. Booysen. "Optimal schedule and temperature control of stratified water heaters." Energy for Sustainable Development 62 (June 2021): 67–81. http://dx.doi.org/10.1016/j.esd.2021.03.009.

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28

Čović, Nikolina, Hrvoje Pandžić, and Yury Dvorkin. "Learning indoor temperature predictions for optimal load ensemble control." Electric Power Systems Research 211 (October 2022): 108384. http://dx.doi.org/10.1016/j.epsr.2022.108384.

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29

Gasser, Ingenuin, Martin Rybicki, and Winnifried Wollner. "Optimal control of the temperature in a catalytic converter." Computers & Mathematics with Applications 67, no. 8 (May 2014): 1521–44. http://dx.doi.org/10.1016/j.camwa.2014.02.006.

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30

Lashin, D. A. "On the existence of optimal control of temperature regimes." Journal of Mathematical Sciences 158, no. 2 (March 14, 2009): 219–27. http://dx.doi.org/10.1007/s10958-009-9386-2.

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31

Kalinda, Chester, Steady Mushayabasa, Moses J. Chimbari, and Samson Mukaratirwa. "Optimal control applied to a temperature dependent schistosomiasis model." Biosystems 175 (January 2019): 47–56. http://dx.doi.org/10.1016/j.biosystems.2018.11.008.

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32

Bavière, R., and M. Vallée. "Optimal Temperature Control of Large Scale District Heating Networks." Energy Procedia 149 (September 2018): 69–78. http://dx.doi.org/10.1016/j.egypro.2018.08.170.

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33

Morimoto, Jun, Yoshinobu Shikanai, Daisuke Obara, Yoshiyuki Yamashita, and Mutsumi Suzuki. "Simple Optimal Regulator for Temperature Control of a CSTR." KAGAKU KOGAKU RONBUNSHU 28, no. 4 (2002): 391–95. http://dx.doi.org/10.1252/kakoronbunshu.28.391.

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34

DHAR, PARITOSH KUMAR, and D. K. SINHA. "Optimal temperature control in hyperthermia by artificial surface cooling." International Journal of Systems Science 20, no. 11 (November 1989): 2275–82. http://dx.doi.org/10.1080/00207728908910303.

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35

Terajima, Yoshimi, and Yasuo Nonaka. "Optimization of Retort Temperature Profile Using Optimal Control Theory." Transactions of the Japan Society of Mechanical Engineers Series C 61, no. 586 (1995): 2387–94. http://dx.doi.org/10.1299/kikaic.61.2387.

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36

Shahrokhi, Mohammad, and Ali Nejati. "Optimal Temperature Control of a Propane Thermal Cracking Reactor." Industrial & Engineering Chemistry Research 41, no. 25 (December 2002): 6572–78. http://dx.doi.org/10.1021/ie0106783.

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37

Yao, Ke, and Furong Gao. "Optimal start-up control of injection molding barrel temperature." Polymer Engineering & Science 47, no. 3 (2007): 254–61. http://dx.doi.org/10.1002/pen.20701.

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38

Costa, Bertinho A., and João M. Lemos. "Optimal control of the temperature in a solar furnace." Optimal Control Applications and Methods 37, no. 3 (February 27, 2014): 466–78. http://dx.doi.org/10.1002/oca.2113.

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39

Kim, Minsung, Satoru Ito, Kenichi Morimoto, and Yuji Suzuki. "D131 High-Speed Transient Temperature Control Using Adjoint-Based Optimal Control Scheme." Proceedings of the Thermal Engineering Conference 2011 (2011): 91–92. http://dx.doi.org/10.1299/jsmeted.2011.91.

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40

Ghanim, Tahani, Ahmed R. Ajel, and Amjad j. Humaidi. "Optimal Fuzzy Logic Control for Temperature Control Based on Social Spider Optimization." IOP Conference Series: Materials Science and Engineering 745 (March 21, 2020): 012099. http://dx.doi.org/10.1088/1757-899x/745/1/012099.

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41

Love, Belinda, Wayne S. Johnson, and George C. J. Fernandez. "A Germination Study of Purple Sage." HortTechnology 4, no. 3 (July 1994): 244–47. http://dx.doi.org/10.21273/horttech.4.3.244.

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Germination of purple sage [Salvia dorrii (Kellogg) Abrams] seed was evaluated under 21 temperature combinations (day temperatures from 5 to 30C and night temperatures from 5 to 30C) in two experiments: 1) cool-moist stratification; and 2) sandpaper scarification, leaching with water, or gibberellic acid (GA3). The quadratic responses of weighted germination percentage (WGP), a combined index of germination percentage and speed of germination, were significant (P ≤ 0.05) for all treatments. The interaction of day and night temperatures was significant (P ≤ 0.05) only for the 2-week stratification treatments and for the Expt. 2 control. Stratification increased WGP over the control. Optimal WGP for all stratification treatments ranged from 46% to 51%. Optimal WGP was the same for both GA3 treatments. Optimal WGP for 0.29 mmol GA3 occurred at 16C night temperature and 22C day temperature, and for the 1.44 mmol GA3 treatment at 18C night and at 30C day temperature.

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42

Ibragimov, Akmaljon, and Muattar Tokhirjonova. "THE IMPACT OF MICROCLIMATE FACTORS ON SILK THICKNESS UNIFORMITY AND OPTIMAL CONTROL THROUGH A MECHATRONIC SYSTEM." American Journal of Applied sciences 05, no. 06 (June 1, 2023): 17–22. http://dx.doi.org/10.37547/tajas/volume05issue06-05.

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This study investigates the influence of microclimate factors on the uniformity of silk thickness and explores the application of a mechatronic system for optimal control and maintenance. As environmental conditions vary on a daily and seasonal basis, managing temperature and relative humidity becomes crucial for consistent cocoon production. The review delves into the significant role of temperature and humidity in the growth and development of silkworms, highlighting the potential of a mechatronic system for regulating the microclimate. Additionally, the research addresses the creation of an optimal microclimate during cocoon wrapping and examines the impact of temperature and humidity on the quality parameters of the resulting cocoon.

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43

GÖTZ, THOMAS, RENE PINNAU, and JENS STRUCKMEIER. "OPTIMAL CONTROL OF CRYSTALLIZATION PROCESSES." Mathematical Models and Methods in Applied Sciences 16, no. 12 (December 2006): 2029–45. http://dx.doi.org/10.1142/s0218202506001807.

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In this paper an optimal control problem for polymer crystallization is investigated. The crystallization is described by a non-isothermal Avrami–Kolmogorov model and the temperature at the boundary of the domain serves as control variable. The cost functional takes into account the spatial variation of the crystallinity and the final degree of crystallization. This results in a boundary control problem for a parabolic equation coupled with two ordinary differential equations, which is treated by an adjoint variable approach. We prove the existence and uniqueness of solutions to the state system as well as the existence of a minimizer for the cost functional under consideration. The adjoint system is derived and we use a steepest descent algorithm to solve the problem numerically. Numerical simulations illustrate the applicability and performance of the optimization algorithm.

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44

Hovorushchenko, Tetiana, Sergii Aleksov, Yurii Popov, and Vyacheslav Bachuk. "DECISION-MAKING METHOD FOR TEMPERATURE CONTROL IN THE SMART HOME." Computer systems and information technologies, no. 3 (September 29, 2023): 6–11. http://dx.doi.org/10.31891/csit-2023-3-1.

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The current challenge is to provide automatic decision support in a smart home. A study of the top solutions of well-known smart homes has shown that existing solutions usually do not provide for fully automatic control in a smart home, but are focused either on automatic control in conjunction with manual control or user-controlled control. Therefore, the goal of this study is to support decision-making for fully automatic temperature control in a smart home. Human well-being and performance depend on the meteorological conditions of the environment in which a person is located. The most important condition for high performance, rest, and health is the creation and maintenance of an optimal home microclimate. One of the main parameters of the indoor microclimate is temperature. The room temperature control subsystem ensures the optimal temperature level and allows for individual adjustment for each family member. The developed rules for determining the optimal room temperature allow you to evaluate the existing temperature parameters for further automatic operation of the smart home temperature control subsystem in residential premises of various types. The purpose of the temperature control subsystem is to provide comfortable conditions in residential premises of various types in terms of their temperature regime. The developed decision-making method for temperature control in a smart home, which is the basis of the smart home temperature control subsystem, provides a comfortable and optimal (taking into account building and sanitary and hygienic standards) temperature in the corresponding living space. The results of the functioning of the smart home temperature control decision-making method have shown that the developed method provides for the recognition of situations (optimal temperature, low temperature, high temperature) and support for decision-making on the temperature regime in a certain type of residential space (turning on heating devices, turning on cooling devices, no action, etc.).

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Wu, Zhao Yu. "Temperature Optimal Control Model Design of the Metal Material Smelting." Applied Mechanics and Materials 716-717 (December 2014): 1699–702. http://dx.doi.org/10.4028/www.scientific.net/amm.716-717.1699.

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The accurate control methods for temperature of metallic materials smelting is studied. For the defect of temperature changes with quite high frequency caused by complicated process during metallic materials smelting process, a temperature optimal control method of the metallic material smelting based on 2T-S fuzzy model is proposed. Temperature state signal is collected by the sensor during the smelting of metallic materials, then filtered and regarded as input data for a 2T-S fuzzy model. 2T-S fuzzy model is established to achieve temperature optimal control during metallic material smelting. The experimental results show that the proposed algorithm can effectively improve the accuracy of the temperature control of metallic materials smelting process, and achieved satisfactory results.

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Hömberg, D., S. Volkwein, and W. Weiss. "Optimal control strategies for the surface hardening of steel." Journal de Physique IV 120 (December 2004): 325–35. http://dx.doi.org/10.1051/jp4:2004120037.

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We discuss control strategies for the surface hardening of steel with laser or electron beam. The goal is to acchieve a prescribed hardening depth avoiding surface melting. Our mathematical model consists of a system of ODEs for the phase volume fractions coupled with the heat equation. The system is solved semi-implicitely using the finite element method. For the optimal control we discuss two approaches: model reduction using POD (Proper Orthogonal Decomposition) and a feedback control of temperature. The numerical results prove that it is not sufficient to control the surface temperature in order to obtain a uniform hardening depth. Instead the best strategy should be to compute the optimal temperature in the hot spot of the beam by solving the control problem and use this temperature as the set-point for the pyrometer control of the real process.

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Wang, Liang, and Shudan Deng. "Optimal Operation Control of Composite Ground Source Heat Pump System." Power Engineering and Engineering Thermophysics 1, no. 1 (October 31, 2022): 64–75. http://dx.doi.org/10.56578/peet010107.

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During the operation of the ground source heat pump (GSHP) system, the operations of the chiller system should be controlled by adjusting the difference between water temperature and wet bulb temperature. Therefore, it is important to consider the control strategy for the switch time (ST) and wet bulb temperature difference (WBTD) of the chiller system. This paper sets up two control strategies, namely, the strategy to control the ST of system operations, and the strategy to control the WBTD. Then, theoretical modeling was carried out to compare the system energy consumption and borehole wall temperature under different strategies. The modeling results were referred to optimize the control strategy for composite GSHP systems. It was found that, under the ST control strategy, the best wet bulb temperature is 2℃, and the best chiller operation hours are 3h; under the WBTD control strategy, the best wet bulb temperature is 3.5℃, and the best WBTD is 1.5℃. In addition, the ST control strategy is superior to the WBTD control strategy, in terms of system energy consumption, borehole wall temperature and initial investment.

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Zheng, Tiegang, Shuangke Sun, Haitao Liu, Qingfu Xia, and Quanli Zong. "Optimal control of reservoir release temperature through selective withdrawal intake at hydropower dam." Water Supply 17, no. 1 (August 11, 2016): 279–99. http://dx.doi.org/10.2166/ws.2016.133.

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This study is motivated by the need to understand the temperature dynamics and warm-water temperature withdrawal. This study also recognizes the need for an environmental assessment of the proposed temperature control schemes at New Fengman Dam. An unsteady three-dimensional (3D) non-hydrostatic model is used in the present study to predict the hydrodynamics and thermal dynamics in the forebay and intakes of the New Fengman Dam. The numerical model is validated using hydrodynamic data collected from a 1:120 entire physical model and 1:30 local model in the present paper. The numerical and experimental results indicate that the Stop Log Gate has no effect on warm-water withdrawal. After dam reconstruction, the reservoir release temperatures can be increased from 4.0 °C to 6.0 °C to improve the habitat of native fishes. The cancellation of the Stop Log Gate program is recommended; the old dam meets the performance objectives for temperature increase.

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Hazyuk, Ion, Christian Ghiaus, and David Penhouet. "Optimal temperature control of intermittently heated buildings using Model Predictive Control: Part II – Control algorithm." Building and Environment 51 (May 2012): 388–94. http://dx.doi.org/10.1016/j.buildenv.2011.11.008.

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Olejár, M., V. Cviklovič, D. Hrubý, and L. Tóth. "Fuzzy control of temperature and humidity microclimate in closed areas for poultry breeding." Research in Agricultural Engineering 60, Special Issue (December 30, 2014): S31—S36. http://dx.doi.org/10.17221/30/2013-rae.

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This contribution describes the ways of temperature and humidity microclimate control in breeding areas using a fuzzy controller. It is focused on poultry, whereby the most important parameters for optimal breeding are temperature and humidity. The main aim was to evaluate the control process according to control quality in the controller’s steady state and the power consumption of the system. The used control algorithm was designed in the Matlab application, and it was practically verified in a closed thermodynamic system. Practical measurements have shown that with an increasing number of fuzzy controller’s interference rules a better control quality in steady states and lower power consumption of the system is achieved.

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