Infrared Drying Process of an Experimental Water Painting: Model Predictive Control

Abstract

This article deals with the experimental control of an infrared drying process of a water based epoxy-amine painting. This approach is based on a unidirectional diffusional modeling of infrared drying phenomena where both heat and mass transfers under shrinkage conditions are accounted for. The control problem is concerned with the tracking of any given trajectory for one of the characteristics (i.e., the temperature or the mean water content) during the drying cycle. This is solved using the well-known model predictive control framework where the nonlinear diffusional model is directly used in the control formulation. Experimental results show the efficiency of the trajectory tracking. This method can be extended for more general constrained control problem.     

A SEMI-THEORETICAL MODEL FOR THE DRYING OF THUMPSON SEEDLESS GRAPES

In this paper, the usefulness of a mathematical model based on equations describing the diffusional phenomena which are variable with time, is developed and discussed in relation to serve as a model for experimental data of drying of Thompson seedless grapes.

This model represents more closely the drying curves tested, than the classic diffusion model normally utilized to analize drying processes     

Nonlinear control of an evaporator using an error trajectory technique

This paper outlines the successful application of an adaptive control method in an industrial environment. The control strategy incorporated MRAC (Model Reference Adaptive Control) using an adaptive PID where the adaptive parameter was estimated using a macroscopic energy balance over the control zone based on the concept of a tracking error trajectory. Success is demonstrated in a plant for sugar production where the formation of candy, due to incorrect management, the steam flow to the evaporators prevented the sugar syrups leaving the system to pass to the centrifugal screens. This stopped production three or four times a day for 30 min, leading to serious problems in relation to cost and quality, the evaporators being very sensitive to temperature changes. © 2000 Society of Chemical Industry     

Model-based multivariable control of the drying of a thin sheet of fibres in a continuous infrared dryer

We developed an Internal Model Control (IMC) algorithm for drying a thin textile fabric, continuously passing through an electric infrared dryer, based on a reduced linear model of the drying dynamics. This model relates the controlled variables, the humidity and temperature of the web at the dryer outlet, to the manipulated variables, the electrical power supplied to the sources and the web speed through the dryer, and also to changes in the initial humidity of the web at the dryer inlet. The control algorithm was first tested by simulation using the model in regulation mode, and in set-point tracking mode, to vary the manipulated variables so as to maintain the controlled variables at their respective set-points when the inlet web temperature and humidity were changed. The performance under simulated operational conditions was compared to that of a conventional feedback proportional-integral (PI) controller coupled with a feedforward control. The IMC controller was then tested directly in regulation mode using a pilot scale infrared dryer, acting simultaneously on the manipulated variables, the emitter power and the web speed, to control the fabric temperature and humidity at the dryer outlet. The experimental results were compared with those from the above feedback-feedforward controller, on the pilot scale dryer. The results have indicated that the closed-loop stability of the process is assured simply by choosing a stable IMC controller. Also, such a controller does not require the design of specific compensators for the strong interactions between variables of the drying process.     

Experimental study of infrared-convective drying of hydrous ferrous sulphate

This study describes the combined drying (convective and infrared) of hydrous ferrous sulphate. The objective is to reduce the free water fraction in order to obtain a loss of 20% of the initial mass. The drying kinetics was investigated for three thin layers of product (0.5, 1, and 2 mm) placed in a rectangular crucible. During the experiment, the upper face of the samples is subjected to infrared irradiation and air flow. Results show that IR irradiation makes it possible to reduce the drying time in an important way and that it is necessary to modulate the infrared irradiation with the thickness. The high amount of IR irradiation applied to the product can generate gradients of moisture in the product. So, the formation of a crust on the surface of the material can be observed and the temperature of the material becomes higher than the melting temperature (64 °C). This crust limits the migration of water towards the surface. It is then necessary to apply appropriate control to the infrared emitters.     

An Anticipatory Terminal Iterative Learning Control Approach with Applications to Constrained Batch Processes

This work presents an anticipatory terminal iterative learning control scheme for a class of batch processes, where only the final system output is measurable and the control input is constant in each operations. The proposed approach works well with input constraints provided that the desired control input with respect to the desired trajectory is within the saturation bound. The tracking error convergence is established with rigorous mathematical analysis. Simulation results are provided to show the effectiveness of the proposed approach.     

ROBUST CONTROL OF BATCH REACTORS

The design of robust nonlinear feedback controller is analysed for a trajectory tracking in a single-input single-output nonlinear state variable system x = f(x) + g(x)u, y=cx which arises in nonlinear chemical processes particularly in batch reactor control problems. Simulation results for the batch reactor temperature tracking problem show the effectiveness of the control scheme and its robustness to modelling errors. The method is also applicable to multi-input multi-output system where the number of inputs is equal to that of outputs. The controller design is also analyzed for situations wrier: the kinetics, the activation energy and Ihe heat of reaction are unknown and also only limited measurement of state-variables are available. The method of Youcef-Toumi and Ito (1987) is applied to such problems and the effectiveness of control system is shown by simulation.     

Robust discrete control of nonlinear processes: Application to chemical reactors

Trajectory tracking or rejecting persistent disturbances with digital controllers in nonlinear processes is a class of problems where classical control methods breakdown since it is very difficult to describe the dynamic behavior over the entire trajectory. In this paper, a model-based robust control scheme is proposed as a potential solution approach for these systems. The proposed control algorithm is a robust error feedback controller that allows us to track predetermined operation profiles while attenuating the disturbances and maintaining the stability conditions of the nonlinear processes. Various numerical simulation examples demonstrate the effectiveness of this robust scheme. Two examples deal with effective trajectory tracking in chemical reactors over a wide range of operating conditions. The third example analyses the attenuation of periodic load in a biological reactor. All examples illustrate the ability of the robust control scheme to provide good control in the face of parameter uncertainties and load disturbances.     

Nanoscale three-dimensional single particle tracking

Single particle tracking (SPT) in biological systems is a quickly growing field. Many new technologies are being developed providing new tracking capabilities, which also lead to higher demands and expectations for SPT. Following a single biomolecule as it performs its function provides quantitative mechanistic information that cannot be obtained in classical ensemble methods. From the 3D trajectory, information is available over the diffusional behavior of the particle and precise position information can also be used to elucidate interactions of the tracked particle with its surroundings. Thus, three-dimensional (3D) SPT is a very valuable tool for investigating cellular processes. This review presents recent progress in 3D SPT, from image-based techniques toward more sophisticated feedback approaches. We focus mainly on the feedback technique known as orbital tracking. We present here a modified version of the original orbital tracking in which the intensities from two z-planes are simultaneously measured allowing a concomitant wide-field imaging. The system can track single particles with a precision down to 5 nm in the x-y plane and 7 nm in the axial direction. The capabilities of the system are demonstrated using single virus tracing to follow the infection pathway of Prototype Foamy Virus in living cells.     

ESTIMATION OF FUNCTIONS IN DRYING EQUATIONS

In drying problem, particularly for drying foodstuff, modelling is very difficult. Many physical effects have to be taken into account for mass transfer ; then mass transfer coefficient varies

In different models unknown functions must be estimated. It is particularly the case in simple models of drying using average values of water content, where the mass transfer varies versus mean water content in falling rate period. On the other hand in the “diffusion model” we have the same problem concerning the diffusion coefficient which must be also estimated

The method we propose in this paper for these two models : simple and “diffusion model” of drying consists from measurements of temperature and water content of the product to search a numerical approach of the unknown function. This method uses optimization techniques on computer and least squares criterion between model values and experimental data

Results are given for the “diffusion model” applied to shelled corn drying to find the diffusion coefficient and for a simple 11107 del applied to plum drying to find the mass transfer coefficient.     

EFFECT OF INFRARED IRRADIATION ON DRYING CHARACTERISTICS OF WET POROUS MATERIALS

ABSTRACT

We studied infrared drying characteristics of wet porous materials by comparison with the convective drying characteristics, and our attention was focused on the factors influencing their characteristics. By selecting three kinds of membrane filters, we examined the influences of the mean pore diameter and the spectral distribution of irradiation power as variables using a far-infrared heater and a near-infrared heater. The differences between the infrared and convective drying characteristics (drying rate, sample temperature, water content distribution) were experimentally obtained, and the influence of mean pore diameter of the sample on its drying characteristics was observed only in infrared drying but in convective drying. By measuring the diffuse transmittance of the membrane filter in consideration of the drying process, we deliberated that infrared radiation penetrating into the drying sample was absorbed directly by the water in the voids, and that the water vaporized there.     

红外干燥不能提高蚕茧的干燥速率

通过大量实验,测定了蚕蛹、茧层的红外吸收图谱,选择相应波长范围的红外涂料和红外灯泡,在不同温度和不同堆放厚度条件下测定了蚕茧的干燥曲线,并与不采用红外线的干燥曲线进行了比较,结果表明红外线未能够提高蚕茧的干燥速率。实验还测定了0.25～25μm范围内单片茧层的红外线透过曲线,结果表明,在所测范围内,红外线的透过率为零,这说明红外线无法穿透茧层。茧层的水分含量很低(约10%),蚕蛹的水分含量很高(约80%),蚕茧干燥的主要目的是除掉蚕蛹中的水分,但茧层包含着蚕蛹,红外线无法穿透茧层对蛹体进行快速干燥。而且,茧层的红外吸收率很低,也不能通过茧层快速吸收红外线热能,然后传给蚕蛹来提高干燥速率,这便是红外线不能提高蚕茧干燥速率的原因。这一结论对国内外蚕业界探讨蚕茧干燥的理论与实践有重要的参考意义。     

Drying and Quality Characteristics of Shredded Squid in an Infrared-Assisted Convective Dryer

Drying is one of the most common methods for processing and preserving squids. A novel forced convective dryer based on infrared heating was developed with an online temperature control. By setting the drying medium temperature of 50°C, we studied the effects of infrared wavelength and air velocity on drying characteristics of the shredded squid and qualities of dried squid products. We also compared it with the conventional hot-air drying (HAD) and advanced microwave vacuum drying (MVD). The infrared heating rate increase was faster than that of HAD. The heating and drying at the wavelength of 2.5–3.0 µm were more effective than those at the infrared wavelength of 5.0–6.0 µm. Specific energy consumption linearly increased with the air velocity. Microstructure observation showed that the infrared-dried rehydrated sample displayed a muscle fiber structure similar to the fresh sample. The infrared-dried squids had less drying shrinkage, brighter color, and better rehydration capacity than HAD products. Their sensory qualities were better than HAD and MVD products. Above all, infrared drying with wavelength of 2.5–3.0 µm and air velocity of 0.5 m/s was suggested as the best drying condition for squids in this study.     

Integrating data‐based modeling and nonlinear control tools for batch process control

A data‐based multimodel approach is developed in this work for modeling batch systems in which multiple local linear models are identified using latent variable regression and combined using an appropriate weighting function that arises from fuzzy c‐means clustering. The resulting model is used to generate empirical reverse‐time reachability regions (RTRRs) (defined as the set of states from where the data‐based model can be driven inside a desired end‐point neighborhood of the system), which are subsequently incorporated in a predictive control design. Simulation results of a fed‐batch reactor system under proportional‐integral (PI) control and the proposed RTRR‐based design demonstrate the superior performance of the RTRR‐based design in both a fault‐free and faulty environment. The data‐based modeling methodology is then applied on a nylon‐6,6 batch polymerization process to design a trajectory tracking predictive controller. Closed‐loop simulation results illustrate the superior tracking performance of the proposed predictive controller over PI control. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

Simultaneous optimization and control for polypropylene grade transition with two-layer hierarchical structure

In this paper, a two-layer hierarchical structure of optimization and control for polypropylene grade transition was raised to overcome process uncertain disturbances that led to the large deviation between the open-loop reference trajectory and the actual process. In the upper layer, the variant time scale based control vector parametric methods (VTS-CVP) was used for dynamic optimization of transition reference trajectory, while nonlinear model predictive controller (NMPC) based on closed-loop subspace and piece-wise linear (SSARX-PWL) model in the lower layer was tracking to the reference trajectory from the upper layer for overcoming high-frequency disturbances. Besides, mechanism about trajectory deviation detection and optimal trajectory updating onlinewere introduced to ensure a smooth transition for the entire process. The proposed method was validated with the real data from an industrial double-loop propylene polymerization reaction process with developed dynamic mechanismmathematicalmodel.     

OPTIMAL CONTROL OF THE PRIMARY AND SECONDARY DRYING STAGES OF BULK SOLUTION FREEZE DRYING IN TRAYS

The problem of operating a tray freeze dryer to obtain a desired final bound water content in minimum time is formulated as an optimal control problem with the use of the rigorous unsteady state mathematical model of Sadikoglu and Liapis [9] that has been found to describe satisfactorily the experimental dynamic behavior of the primary and secondary drying stages of bulk solution freeze drying of pharmaceuticals in trays. The heat input to the material being dried and the drying chamber pressure are considered to be control variables. Constraints are placed on the system state variables by the melting and scorch temperatures during primary drying, and by the scorch temperature during secondary drying. Necessary conditions of optimality for both the primary and secondary drying stages are derived and presented, and an approach for constructing the optimal control policies that would minimize the drying times for both the primary and secondary drying stages, is presented. The theoretical approach presented in this work was applied in the freeze drying of skim milk, and significant reductions in the drying times of primary and secondary drying were obtained, when compared with the drying times obtained using the operational policies reported in the literature, by using the optimal control policies constructed from the theory presented in this work. Furthermore, it is shown that the optimal control policy leads to the desired in practice result of having at the end of secondary drying temperature and bound water concentration profiles (in the dried layer) whose gradients are very small. It is also shown that by using the optimal control policy and an excipient capable of increasing the melting temperature without affecting product quality, one can significantly reduce the drying time of the primary drying stage.     

Iterative learning controller synthesis using FIR models for batch processes

Adaptive iterative learning control based on the measured input-output data is proposed to solve the traditional iterative learning control problem in the batch process. It produces a control law with self-tuning capability by combining a batch-to-batch model estimation procedure with the control design technique. To build the unknown batch operation system, the finite impulse response (FIR) model with the lifted system is constructed for easy construction of a recursive least squares algorithm. It can identify the pattern of the current operation batch. The proposed model reference control method is applied to feedback control of the lifted system. It finds an appropriate control input so that the desired performance of the batch output can track the prescribed finite-time trajectory by iterative trials. Furthermore, on-line tracking control is developed to explore the possible adjustments of the future input trajectories within a batch. This can remove the disturbances in the current batch rather than the next batch trial and keep the product specifications consistent at the end of each batch. To validate the theoretical findings of the proposed strategies, two simulation problems are investigated.