Optimal Temperature Control Research Articles

Automation of Squid Based Vibrating Sample Magnetometer using Labview

The operation of the SQUID based vibrating sample magnetometer has been fully automated using LabVIEW.Personal computer is used to interface with a large number of electronic instruments and modules to effectively and comprehensively control the measurement process. The computer controls the stepper motor to locate the sample at the position corresponding to maximum sensitivity and uses a temperature controller to sweep the sample temperature at user desired heating rate by automatically setting parameters to the values which are necessary for optimal temperature control. SQUID output, which is proportional to magnetization of the sample, is phase sensitively detected using a lock in amplifier referenced to the vibration frequency and the measured data is stored in the computer for subsequent analysis. Provision exists for an online display of the plot of magnetization as a function of temperature as the data is acquired. The automation of the SQUID VSM greatly reduces the time required for the magnetization measurement and eliminates the possibility of human errors.

Optimal temperature control of intermittently heated buildings using Model Predictive Control: Part II – Control algorithm

Abstract The goal of optimal temperature control in buildings is usually to ensure thermal comfort with minimal energy consumption. In intermittently occupied buildings, this presumes the ability of the controller to recover in due time the building from setback. Model Predictive Control (MPC) is considered among the best candidates for this task due to its ability to use occupancy schedule and weather forecasts for optimal temperature control. However, the use of the classical cost function within MPC does not allow to achieve the objectives of minimal energy consumption and optimal restart of the heating system. Therefore, a new cost function is introduced, which minimizes the energy consumption while maintaining the thermal comfort in the building. The obtained linear optimization problem is formulated to fit into the canonical form of Linear Programming method.

Optimal temperature control of intermittently heated buildings using Model Predictive Control: Part I – Building modeling

Abstract An important performance in building thermal control is to ensure thermal comfort with minimal energy consumption. Model Predictive Control (MPC) is considered to be one of the most suited solutions for this due to its ability to use occupancy schedule and weather forecasts for optimal temperature control. MPC relies on a dynamical model of the building, which is the main difficulty of applying it. Therefore, this paper treats the problems related to building modeling and model parameters identification. A robust model of the building is obtained in two stages: firstly physical knowledge is used to determine the structure of a low-order model, then least squares identification method is applied to find the numerical values of the model parameters. In order to perform the identification usually there are required input/output data records having variations which generally are not accepted in inhabited buildings because of imposed comfort conditions. Also inhabited buildings contain unmeasured disturbance sources which may degrade the identified model quality. Therefore this paper proposes to use detailed building models, implemented in dedicated simulation tools, to generate the required input/output data records instead of measuring them on real buildings. This allows us to apply desired input signals and to eliminate disturbance sources. Additionally, the paper presents a method to identify the nonlinearity existing in building thermal behavior, which permits to represent the building by separated linear and nonlinear blocks. This model representation, used along with the linearization method proposed in Part II, permits to design the temperature controller without resorting to the nonlinear system theory.

New Perspective to Continuous Casting of Steel with a Hybrid Evolutionary Multiobjective Algorithm

In this article, we present a new perspective in solving computationally demanding problems such as the optimal control of the continuous casting of steel. We consider a multiobjective formulation of the optimal control of the surface temperature of the steel strand with five objectives, where constraint violations are minimized as objectives because no feasible solutions exist otherwise. A hybrid evolutionary multiobjective algorithm (HNSGA-II) is used to overcome discrepancies of evolutionary multiobjective optimization algorithms such as slow convergence and lack of convergence proof to the Pareto front. HNSGA-II uses NSGA-II as an underlying evolutionary multiobjective algorithm and an achievement scalarization function to scalarize objective functions for local search, which improves the population and speeds up the convergence. This is important because most evolutionary multiobjective algorithms are known to have difficulties with five objective functions. The algorithm is used to generate a set of Pareto solutions showing different trade-offs. However, it is difficult to generate Pareto solutions showing all the different trade-offs with a finite small population size. Hence, we use the preference information related to constraint violations in the weights of the achievement scalarization function to generate solutions with different trade-offs in preferable regions of the Pareto front. In addition, we use clustering and present typical solutions of different clusters so that the most preferred solution to be implemented can easily be identified. We demonstrate the approach and compare the results to previous studies.

Optimal PID Control of Heat Exchanger Temperature

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.

A study on an optimal approach temperature control strategy of condensing water temperature for energy saving

An optimal approach temperature (OAT) control strategy is proposed for resetting the condensing water temperature hourly, so to maximize the performance of the combined water chiller and cooling tower system. A system performance factor is introduced for evaluation of the system performance. A regression function is presented for the calculation of an optimal condensing water temperature at each hour of air-conditioning operation. The parameters in the regression function include the ambient wet bulb temperature, the chiller load ratio at the hour, and a dimensionless relative efficiency of chiller and cooling tower. The regression function has an R 2 close to 1 compared to the computed results. When applied to two cities in Taiwan, the OAT control strategy has a potential to save energy more than 4% on an annual basis. The OAT control strategy is most advantageous when applied to regions with large seasonal variation of wet bulb temperature.

Model-Based Control for Rapid Thermal Processing of Semiconductor Wafers

In this paper, a model-based control method for RTP (Rapid Thermal Processing) system is proposed. RTP system is a device used to heat semiconductor wafers uniformly. It can heat wafers rapidly and reduce the processing time. However, it is very difficult for a RTP system to achieve the extremely stringent requirement on temperature uniformity (±1[K] or less) without suitably controlling and coordinating the radiative heat flux from the halogen lamps. In this research, the location of lamps is optimized first. Then, a feedback control system is designed which provides optimal temperature control during the thermal processing. The design is carried out based on a linearized model and H2 optimal control. The effect of sensor location is also investigated. Numerous simulations show that satisfactory performances are obtained in both the tracking and the uniformity of wafer temperature.

The Optimal Temperature Control for the Reactions with Parallel Deactivation of Enzyme Encapsulated inside Microorganism Cells

A batch biotransformation process running in the presence of microorganisms cells revealing a specified enzyme activity has been considered. A non-linear deactivation model suggested by Do and Weiland has been taken into account for modeling of the process. Based on variational calculus computations aimed at finding an optimal selection of temperature conditions that ensure obtaining maximum conversion or minimum duration time necessary for its attaining have been carried out. The solutions were given and discussed for the stationary process, and for the active upper and lower temperature limitations. It has been proved that an application of microorganisms cells results in slowing down the reaction rate and shifting the initial temperature of the stationary profile to higher values. They are more pronounced the lower the permeability of the cell membrane is. In consequence, an extension of the process duration time is observed along the sections of the optimal profile while the lower temperature constraint usually becomes inactive.

ADAPTIVE CONTROL OF TEMPERATURE FOR MINIMIZATION OPERATING COSTS OF INDUSTRIAL METHANE TANK PROCESS

An algorithm for adaptive control of temperature in methane tank is developed in order to minimize operating costs under variation of the methane tank process conditions. The adaptation is based on process model and on-line minimization of objective function that relates operating costs to the process variables. Mathematical model for prediction of biogas production and simulation of the temperature control process is identified using experimental data from the waste water treatment plant. The temperature adaptive control system is investigated via computer simulation of the control system performance under operating conditions of real methane tank process during one year period. The process operating costs by optimal control of temperature are compared to those of temperature control at constant set-point. The model identification and the control system simulation results are presented and discussed.

Optimal Control of Temperature in Fluid Flow Using Four Types of MinimizationTechniques

The purpose of this paper is a thermal optimal control problem using four types of minimization technique. The four types of minimization techniques are the weighted gradient method, the Newton based method, the modified steepest descent method and the steepest descent method using weighting adaptation. The formulation is based on the optimal control theory in which the performance function is expressed by the computed and targeted temperatures. The optimal values can be obtained by minimizing the performance function. The thermal fluid flow is described by the Boussinesq approximated incompressible Navier-Stokes equation and the energy equation is analyzed. BFGS is applied to calculate the Hessian matrix which is used in the Newton-based method. The traction given by the perturbation for the Lagrange multiplier is used in the BFGS method.

Optimal temperature control in a batch bioreactor with parallel deactivation of enzyme

A biotransformation process with parallel deactivation of biocatalyst running in a batch reactor has been analyzed. A non-linear deactivation model suggested by Do and Weiland has been taken into account. Based on variational calculus analytical computations aimed at finding an optimal selection of temperature conditions that ensure obtaining maximum conversion or minimum duration time necessary for its attaining have been carried out. Solutions for a stationary process and that carried out at the active upper and lower temperature limitations have been presented. Furthermore, an analysis of the course of the process under isothermal conditions as those indispensable for the appropriate choice of the optimal conditions has been presented. Based on an example of hydrogen peroxide decomposition process in the presence of the native catalase of yeast Saccharomyces cerevisae (CSC) the obtained solution has been described. In addition an influence of the quotient of energy of deactivation and reaction processes, initial and final biocatalyst activity and conversion on the course of the optimal temperature profiles have been considered. It has been proved that a decrease in the activation energy quotient and the final biocatalyst activity as well as an increase in conversion results in an increase of the overall process duration time. Also a comparison of the course of the stationary temperature profiles at different ranges of substrate concentration and the effect of the latter on the analyzed objective function has been made. It has been revealed that in case of processes which run at any range of the substrate concentrations, in order to achieve the shortest duration time of their course, it is appropriate to conduct them at possibly the lowest concentration range.

Optimal Body Temperature in Transitional Extremely Low Birth Weight Infants Using Heart Rate and Temperature as Indicators

To explore body temperature in relationship to heart rate in extremely low birth weight (ELBW) infants during their first 12 hours to help identify the ideal set point for incubator control of body temperature. Within subject, multiple-case design. A tertiary neonatal intensive care unit (NICU) in North Carolina. Ten infants born at fewer than 29 weeks gestation and weighing 400 to 1,000 g. Heart rate and abdominal body temperature were measured at 1-minute intervals for 12 hours. Heart rates were considered normal if they were between the 25th and 75th percentile for each infant. Abdominal temperatures were low throughout the 12-hour study period (mean 35.17-36.68 degrees C). Seven of 10 infants had significant correlations between abdominal temperature and heart rate. Heart rates above the 75th percentile were associated with low and high abdominal temperatures; heart rates less than the 25th percentile were associated with very low abdominal temperatures. The extent to which abdominal temperature was abnormally low was related to the extent to which the heart rate trended away from normal in 6 of the 10 infants. Optimal temperature control point that maximized normal heart rate observations for each infant was between 36.8 degrees C and 37 degrees C. Hypothermia was associated with abnormal heart rates in transitional ELBW infants. We suggest nurses set incubator servo between 36.8 degrees C and 36.9 degrees C to optimally control body temperature for ELBW infants.

CERTOMAT® CTplus: a purpose-built incubator shaker for mammalian cell cultures

Precise temperature control, stable CO2 concentration and a humidified atmosphere are essential for long-term cultivation of mammalian cells. This could not be achieved until now for agitated cultures. The CERTOMAT®CTplus ensures optimal temperature control and even temperature distribution combined with a controlled humidified atmosphere.

Optimized temperature control system integrated into a micro direct methanol fuel cell for extreme environments

This paper reports a micro direct methanol fuel cell (μDMFC) integrated with a heater and a temperature sensor to realize temperature control. A thermal model for the μDMFC is set up based on heat transfer and emission mechanisms. Several patterns of the heater are designed and simulated to produce a more uniform temperature profile. The μDMFC with optimized temperature control system, which has better temperature distribution, is fabricated by using MEMS technologies, assembled with polydimethylsiloxane (PDMS) material and polymethylmethacrylate (PMMA) holders, and characterized in two methods, one with different currents applied and another with different methanol velocities. A μDMFC integrated with the heater of different pattern and another one with aluminum holders, are assembled and tested also to verify the heating effect and temperature maintaining of packaging material. This work would make it possible for a μDMFC to enhance the performance by adjusting to an optimal temperature and employ in extreme environments, such as severe winter, polar region, outer space, desert and deep sea area.

OPEN-LOOP OPTIMAL TEMPERATURE CONTROL IN GREENHOUSES

Earlier research has revealed that considerable energy savings can be achieved by maintaining an average temperature in the greenhouse in stead of maintaining rigid pre-defined temperature `blue-prints?. A model based optimal control approach has proven to be a suitable framework to tackle these kind of control problems and it has been shown that these algorithms can be implemented on-line. But, when on-line optimal temperature control is considered, interesting questions arise, some of which are still unresolved. The issue tackled in this paper concerns the relation between the resolution of the control strategy (sample time) and energy savings of the control strategy. One would expect that an accurate and frequent anticipation to changing outdoor climate conditions might result in reduced energy consumption. It was indicated in the literature that a sample-time of 0.25 h or 1 hour should be sufficient, but these choices were hardly motivated. In this research, the relation between the control resolution and energy savings was quantitatively investigated using a dynamic greenhouse climate model and measurements of Dutch outdoor climate conditions containing high-frequency components. The results indicate that for an open-loop optimal control problem concerning the realization of an average temperature during a fixed period of one day using a minimum amount of energy with full a-priori knowledge of the outdoor weather, a resolution of the heating profile between half an hour and a hour suffices to produce accurate results in terms of energy conservation. These results were not much affected by parameter variations (heat capacity of the air, the solar heating efficiency) or opening and closing of thermal screens.

Hydrogen production in a thermal plasma hydrogen reformer using ethanol steam reforming

This paper presents both analytical thermodynamic analysis and experimental results of ethanol steam reforming in a thermal plasma reformer at various working conditions. Since our thermal plasma reformer can work well at atmospheric pressure, a thermodynamic equilibrium prediction is first performed at temperatures in the range from 500 to 1000°C and at mole flow ratios of ethanol to water from 1:1 to 1:6. And then the experiment for ethanol steam reforming of a fabricated thermal plasma reformer is performed and the reformate stream is immediately analyzed using GC/MS, GC/FID/TCD, and pre‐concentrator. Comparing predicted data with experimental data, an optimal working condition is determined at the temperature of 750°C and at mole flow ratio of ethanol to water of 1:3. In the future, an optimal temperature control system will be designed to maintain the thermal plasma reformer at the temperature of 750°C under the inlet mole flow ratio of ethanol to water of 1:3.

Energy saving strategies in air-conditioning for museums

In the museum environment a strict thermal-hygrometric control is necessary primarily for the correct artwork conservation and then for the visitor thermal comfort. Considering that the air-conditioning system has to operate constantly, suitable techniques permit to obtain useful energy savings, allowing, however, a good dynamic microclimatic control. In this paper a case study is presented about various strategies used to reduce energy requirements for HVAC systems in an exhibition room of a modern museum. Using the dynamic simulation code DOE 2.2 and typical climatic hourly data sets, the annual energy use for an all-air system has been calculated, as well as the savings obtainable using different techniques, such as dehumidification by adsorption (desiccant wheel – saving equal to 15% with respect to a base configuration), total energy recovery from the relief air (passive desiccant – 15%), outdoor airflow rate variation (demand control ventilation – 45%). Moreover, the correspondence has been analyzed between the energy request and the admitted variation of indoor temperature and relative humidity: changing the admitted indoor RH range from 50 ± 2% to 50 ± 10%, energy savings around 40% have been obtained. As regards the thermal-hygrometric performance, an optimal control of temperature has been guaranteed with all the configurations, while the best performance in RH control has been obtained with the desiccant system. Considering a simple payback analysis, if the artworks preserved in a museum are particularly sensitive to indoor humidity variation, a desiccant system should be properly used; on the contrary, when the indoor humidity control is not strongly needed, the use of a HVAC system with demand control ventilation is advisable, because of the lowest payback value. The system with total energy recovery presents intermediate features.

냉장 컨테이너 내부의 공기유동 및 열전달 현상에 대한 CFD 시뮬레이션

To prevent deterioration of agricultural products during cold transportation, optimized temperature control is essential. Because the control of temperature and thermal uniformity of transported products are mainly governed by cooling air flow pattern in the transportation equipment, the accurate understanding and removal of appearance of stagnant air zone by poor ventilation is key to design of optimized cooling environment. The objectives of this study were to develop simulation model to predict the airflow and heat transfer phenomena in the cold container and to evaluate the effect of fan blowing velocity on the temperature level and uniformity of products using the CFD approach. Comparison of CFD prediction with PIV measurement showed that RSM turbulent model reveals the more reasonable results than standard <TEX>$k-{\varepsilon}$</TEX> model. The increment of fan blowing velocity improved the temperature uniformity of product and reduced almost linearly the averaged temperature of product.

Temperature Control of a Bench‐Scale Batch Polymerization Reactor for Polystyrene Production

AbstractBatch polymerization reactors commonly use optimal temperature control as the strategic operation parameter. This strategy allows for better operability and a more economic process. The main objective of the batch polymerization reactor control is to obtain acceptable product quality. Direct measurement of polymer quality is rarely achievable, which makes the online control of the reactor difficult. Temperature is the most controllable operational variable in the polymer reactor, which is seen to have a direct effect on the polymer properties. Temperature is chosen as the set point by using either the isothermal temperature or optimal temperature trajectory. Online control of the optimal temperature profile of a bench‐scale batch polymerization reactor was experimentally investigated in this study. The temperature trajectory was used as the target for controllers to follow. The time‐profile temperature was obtained with the objective of obtaining the desired conversion and number‐average chain length within the minimum time. Two advanced controls of fuzzy logic control and generic model control were applied to the polymer reactor. A comparison of the controllers reveals that both performed better than conventional controllers.

Robust optimal control of polymorphic transformation in batch crystallization

AbstractOne of the most important problems that can arise in the development of a pharmaceutical crystallization process is the control of polymorphism, in which there exist different crystal forms for the same chemical compound. Different polymorphs can have very different properties, such as bioavailability, which motivates the design of controlled processes to ensure consistent production of the desired polymorph to produce reliable therapeutic benefits upon delivery. The optimal batch control of the polymorphic transformation of L‐glutamic acid from the metastable α‐form to the stable β‐form is studied, with the goal of optimizing batch productivity, while providing robustness to variations in the physicochemical parameters that can occur in practice due to variations in contaminant profiles in the feedstocks. A nonlinear state feedback controller designed to follow an optimal setpoint trajectory defined in the crystallization phase diagram simultaneously provided high‐batch productivity and robustness, in contrast to optimal temperature control strategies that were either nonrobust or resulted in long‐batch times. The results motivate the incorporation of the proposed approach into the design of operating procedures for polymorphic batch crystallizations. © 2007 American Institute of Chemical Engineers AIChE J, 2007