Model-based Temperature Control Research Articles

A state-space model-based temperature control system for laser remanufacturing molten pool

ABSTRACT Laser remanufacturing is a key technology for remanufacturing, which has been widely used in aerospace, metallurgy, energy and other fields. However, the problem of shape control has been the bottleneck that restricts the scale and industrial application. In the laser remanufacturing process, the molten pool temperature is the critical to determine the shape and performance stability of remanufactured parts. Based on this, the paper proposes a real-time online control method for laser remanufacturing molten pool temperature based on state space model, which solves the problem of difficult to establish control mechanism model and multiple variable constraints. Develop a real-time online control system for molten pool temperature of laser remanufacturing process based on state space model and incremental integral separation PID control, which uses a single sampling point as temperature feedback, solving the problem of lag generated by traditional feedback cycle, realizing real-time online control of molten pool temperature of laser remanufacturing process. Finally, the experimental results show that the developed molten pool temperature control system can effectively eliminate the sudden and gradual temperature change in the deposition process and significantly improve the thermal accumulation phenomenon in the deposition process, thus improving the forming quality and performance stability of remanufactured parts.

Dynamic compact thermal models for skin temperature prediction of portable electronic devices based on convolution and fitting methods

In most portable electronic devices, besides the temperature of multiple heat sources, i.e. junction temperature, the temperature of the enclosure, i.e. skin temperature, should also be controlled to protect the user experience. Thus, generating the device-level compact thermal model for predicting the skin temperature will not only improve the efficiency of early-stage thermal design but also help to develop the model-based temperature control strategy. However, most of the existing modeling methods mainly focus on predicting the junction temperature. In this paper, the dynamic compact thermal models of two portable electronic devices, including a smartphone and laptop, are first generated based on the convolution method. Under the assumption of linear time-invariant (LTI) systems, the skin temperature of the two test devices could be fast calculated once the step response of each heat source is obtained. The results show that compared to the computational fluid dynamics (CFD) model generated in ANSYS Icepak, the transient deviation of the convolution-based model is within 5%. Then, a linear fitting model is proposed to real-time predict the skin temperature of laptops. Both the experimental and simulation results demonstrate that once the scale factors are trained, the linear fitting model could accurately real-time predict the skin temperature after 60s. The maximum transient deviation in the experiment and simulation are 4% and 7% respectively. The results indicate that the proposed modeling method has tremendous potential for both thermal design and control optimization.

Model-Based Temperature Control in Thermal Processing of Silicon Wafers

The paper proposes a model-based control approach for thermal processing of silicon wafers such as rapid thermal processing. Heating of the wafer is achieved with a large number of high-power LEDs which enable targeted heating over the entire spatial domain. Taking advantage of this feature, a distributed PI controller is first designed assuming an idealized distributed input. This control signal is then approximated by the actual control that enters the system through shape functions using an optimization procedure. A formal analysis of the input-to-state stability with respect to the actuator error, extension with an anti-windup scheme and an experimental validation of the proposed approach are presented.

Compact Piecewise Linear Model Based Temperature Control of Multicore Systems Considering Leakage Power

Temperature control of the new-generation integrated multicore system is challenging. This is because the leakage power, which is significant in modern systems, is nonlinearly related to temperature, resulting in a complex nonlinear control problem in thermal management. In this article, a new dynamic thermal management (DTM) method with compact piecewise linear (PWL) model based predictive control is proposed to solve the nonlinear control problem. First, a compact PWL thermal model, which takes dynamic power as input, is built by combining multiple local compact linear thermal models expanded at several Taylor expansion points. These local compact linear thermal models are obtained by sampling-based model order reduction with high accuracy. Their Taylor expansion points are selected by a systematic scheme, which exploits the thermal behavior property of the multicore chips. Based on the compact PWL thermal model, a new predictive control method is proposed to compute the future power recommendation for DTM. By approximating the nonlinearity accurately with the compact PWL thermal model and being equipped with predictive control technique, the new DTM achieves an overall high quality temperature management with smooth and accurate temperature tracking. Experimental results show that the new method outperforms the linear model predictive control based method and the echo state network based predictive thermal management method in temperature management quality with lower computing overhead.

Model-based temperature control for improving lactic acid production from glycerol.

To maximize the final lactic acid productivity and concentration, temperature control was optimized using a mathematical modelling approach. A kinetic model, including cell growth, product formation and substrate consumption equations, was proposed to describe the lactic acid production process by Escherichia coli AC-521 with glycerol as the substrate. By constructing four functions, the temperature effect was introduced on the fermentation process, where four parameters (Xmax, μmax, Yps and β) were observed to be significantly affected by the temperature. For the convenience of application, the temperature control strategies were simplified by dividing the whole fermentation process into several units. In each unit, the temperature was controlled constantly. Based on the model, the optimal temperature for each unit was determined to maximize the final lactate productivity. This temperature control strategy can be effectively applied in batch and fed-batch cultures, and the verified experimental evaluation showed a good correlation with the model data. Under improved temperature control conditions, a maximal lactic acid concentration of 90.4 g L−1 was obtained after 80 h of fed-batch fermentation, giving a productivity of 1.13 g L−1 h−1, which is 1.2 times more than that in the conventional constant temperature during the cultivation course.

Adaptive model-based temperature control in friction stir welding

The welding temperature strongly affects the quality of friction stir welds. Thus, a novel approach for a closed-loop temperature control system was developed and is described in this paper. A model-based $\mathcal {L}$ 1 adaptive controller was implemented to control the welding temperature during friction stir welding (FSW). This control structure was selected due to its fast adaption to fluctuations in the behavior of the controlled system while guaranteeing robustness of the closed-loop system. A semi-analytical process model, which links the process torque and the welding temperature, was developed and included in the control structure. Thereby, the dynamics of the closed-loop system could be improved. The developed control strategy was compared to the state-of-the-art strategies. The results showed that the developed control structure provides the possibility to reduce the settling time of the closed-loop system while avoiding stability problems. Finally, the effectiveness of the controller was shown during FSW of aluminum to copper.

Model-based temperature control of a diesel oxidation catalyst

The problem studied in this article is the control of a DOC (diesel oxidation catalyst) as used in aftertreatment systems of diesel vehicles. This system is inherently a distributed parameter system due to its elongated geometry where a gas stream is in contact with a spatially distributed catalyst. A first contribution is a model for the DOC system. It is obtained by successive simplifications justified either experimentally (from observations, estimates of orders of magnitude) or by an analysis of governing equations (through asymptotic developments and changes of variables). This model can reproduce the complex temperature response of DOC output to changes in input variables. In particular, the effects of gas velocity variations, inlet temperature and inlet hydrocarbons are well represented. A second contribution is a combination of algorithms (feedback, feedforward, and synchronization) designed to control the thermal phenomena in the DOC. Both contributions have been tested and validated experimentally. In conclusion, the outcomes are evaluated: using the approach presented in this article, it is possible to control, in conditions representative of vehicle driving conditions, the outlet temperature of the DOC within ±15 °C.

Model-Based Temperature Control of Cooking Appliance Using Soft Sensor

In this paper, a model-based temperature control method for cooking appliances is proposed. Due to structural and sanitary limitations, no sensor for the temperature of the cooking object is equipped in general. After constructing a state space model for the heating process and identifying the model parameters for each distinct volume of the cooking object, a state observer is designed. By using this observer as a softsensor, feedback temperature control is implemented instead of the conventional model-less on-off pattern control. Its high tracking performance is demonstrated via numerical examples and experiments.

Modelbased Temperature Control for Improved Fuel Economy of SI Engines

The cooling system of an SI engine has been fitted with an electrically driven waterpump and an electric bypass valve. The control system has two inputs, the coolant mass flow through the pump and the position of the valve bypassing the radiator. The two inputs enable the controller not only to control the temperature of the coolant flowing out of the engine but the temperature of the coolant entering the engine as well. For this multivariable system with two inputs and two outputs a model has been derived. Based on the model obtained a feedforward as well as a feedback controller were designed. The main task of the feedforward controller is the correct closing of the bypass valve at cold start as a function of the demanded value for the engine out temperature and of the observed values of the engine block and engine wall temperatures.Measurements conducted on a dynamic testbench show fuel efficiency improvements of up to 4.5% for a cold start with constant engine operating points. Measurements for the MVEG-A test cycle show a reduction in fuel consumption of 3%. This improvement is due to the higher engine temperatures at which the engine is now operated and the faster rise of the temperature at the beginning, both causing less internal friction.

Model-based temperature control in ovens

The performance of an oven cavity is improved by implementing more advanced control algorithms to the unit. This improvement is necessary to cope with the more stringent requirements of the food market. It is shown with experimental results that the dynamic behavior of the oven cavity is modified significantly through the implementation of a model-based tuned P.I.D. controller. For this purpose, a mathematical model representing the main temperature dynamics of the oven cavity, is identified and validated. Afterwards, this mathematical model is used for tuning of the controller parameters, which allows a fast, safe and inexpensive off-line search for the optimal parameter set. In addition, the effect of practical constraints such as bounds and discretization effects can be examined quite easily. The model-based tuning approach for temperature control of an oven cavity is found to be successful. The application also illustrates the use of advanced measurement and control hardware and software.

Model Based Temperature Control in RTP Yielding ±0.1 °C accuracy on A 1000 °C, 2 second, 100 °C/s Spike Anneal

ABSTRACTA Model Based Control method is presented for accurate control of RTP systems. The model uses 4 states: lamp filament temperature, wafer temperature, quartz temperature and TC temperature. A set of 4 first order, nonlinear differential equations describes the model. Feedback is achieved by updating the model, based on a comparison between actual (measured) system response and modeled system response.

Model-Based Temperature Control of Fed-Batch Reactors

The temperature control of an autoclave with a cooling jacket is studied. Since the heat removal is limited the temperature is controlled by the feed rate of one of the reactants and the full cooling capacity is applied in the safe region of operation. Approaching the runaway region the reactant feed is stopped and the flow rate of the cooling liquid is manipulated. The algorithm is based on a tendency model derived from a first principle one. It includes the system variables (manipulated, measured, controlled, etc.) and parameters (a priori ones and others estimated from the process measurements).