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Title: Advanced control strategies for fluidized bed dryers

Abstract

Generating the best possible control strategy comprises a necessity for industrial processes, by virtue of product quality, cost reduction and design simplicity. Three different control approaches, namely an Input-Output linearizing, a fuzzy logic and a PID controller, are evaluated for the control of a fluidized bed dryer, a typical non-linear drying process of wide applicability. Based on several closed loop characteristics such as settling times, maximum overshoots and dynamic performance criteria such as IAE, ISE and ITAE, it is shown that the Input-Output linearizing and the fuzzy logic controller exhibit a better performance compared to the PID controller tuned optimally with respect to IAE, for a wide range of disturbances; yet, the relevant advantage of the fuzzy logic over the conventional nonlinear controller issues upon its design simplicity. Typical load rejection and set-point tracking examples are given to illustrate the effectiveness of the proposed approach.

Authors:
; ;
Publication Date:
Research Org.:
National Technical Univ. of Athens (GR)
OSTI Identifier:
20006230
Resource Type:
Journal Article
Resource Relation:
Journal Name: Drying Technology; Journal Volume: 17; Journal Issue: 10; Other Information: PBD: Nov 1999
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; DRYERS; FLUIDIZED BEDS; PROCESS CONTROL; CONTROL SYSTEMS; PERFORMANCE; COMPARATIVE EVALUATIONS; ENERGY EFFICIENCY

Citation Formats

Siettos, C.I., Kiranoudis, C.T., and Bafas, G.V. Advanced control strategies for fluidized bed dryers. United States: N. p., 1999. Web. doi:10.1080/07373939908917683.
Siettos, C.I., Kiranoudis, C.T., & Bafas, G.V. Advanced control strategies for fluidized bed dryers. United States. doi:10.1080/07373939908917683.
Siettos, C.I., Kiranoudis, C.T., and Bafas, G.V. 1999. "Advanced control strategies for fluidized bed dryers". United States. doi:10.1080/07373939908917683.
@article{osti_20006230,
title = {Advanced control strategies for fluidized bed dryers},
author = {Siettos, C.I. and Kiranoudis, C.T. and Bafas, G.V.},
abstractNote = {Generating the best possible control strategy comprises a necessity for industrial processes, by virtue of product quality, cost reduction and design simplicity. Three different control approaches, namely an Input-Output linearizing, a fuzzy logic and a PID controller, are evaluated for the control of a fluidized bed dryer, a typical non-linear drying process of wide applicability. Based on several closed loop characteristics such as settling times, maximum overshoots and dynamic performance criteria such as IAE, ISE and ITAE, it is shown that the Input-Output linearizing and the fuzzy logic controller exhibit a better performance compared to the PID controller tuned optimally with respect to IAE, for a wide range of disturbances; yet, the relevant advantage of the fuzzy logic over the conventional nonlinear controller issues upon its design simplicity. Typical load rejection and set-point tracking examples are given to illustrate the effectiveness of the proposed approach.},
doi = {10.1080/07373939908917683},
journal = {Drying Technology},
number = 10,
volume = 17,
place = {United States},
year = 1999,
month =
}
  • The limits of existence of various turbulent and forced fluidization regimes are conditionally indicated. The principal structural parameters of fluidized bed dryers are determined as a function of the characteristics of the material to be dried.
  • Precious work has shown that it is possible to predict the size of a continuous well-mixed fluidized bed dryer from batch drying curve measurements. This approach has been extended in the present study to include energy consumption calculations. A computer code was written to simulate the performance of the dryer and to determine its specific energy consumption E{sub s}. Starting in this case with an isothermal bed batch drying curve, the program first calculates the mean solids residence time required under specified operating conditions. Mass and energy balances are then used to calculate the heat duty and E{sub s}. Themore » bed temperature was found to have a significant effect on specific energy consumption in all cases. However, the influences of air flowrate and humidity, and of solids loading, were shown to depend on the solids drying characteristics.« less
  • Design of fluidized bed dryers constitutes a mathematical programming problem involving the evaluation of appropriate structural and operational process variables so that total annual plant cost involved is optimized. The increasing need for dehydrated products of the highest quality, imposes the development of new criteria that, together with cost, determine the design rules for drying processes. Quality of dehydrated products is a complex resultant of properties characterizing the final products, where the most important one is color. Color is determined as a three-parameter resultant, whose values for products undergone drying should deviate from the corresponding ones of natural products, asmore » little as possible. In this case, product quality dryer design is a complex multi-objective optimization problem, involving the color deviation vector as an objective function and as constraints the ones deriving from the process mathematical model. The mathematical model of the dryer was developed and the fundamental color deterioration laws were determined for the drying process. Non-preference multi-criteria optimization methods were used and the Pareto-optimal set of efficient solutions was evaluated. An example covering the drying of sliced potato was included to demonstrate the performance of the design procedure, as well as the effectiveness of the proposed approach.« less
  • A fluid bed dryer simulator was developed under Excel 5 with Visual Basic for Applications environment. The simulator is based on a mathematical model describing heat and mass transfer in the dryer. The total model incorporates empirical models for the Drying Constant and the Residence Time. These empirical models are crucial in the total model efficiency. Thus a procedure for updating the parameters of the empirical models is provided. This procedure constitutes the learning property of the simulator. Two databases are supplied. The first contains laboratory drying data and it is used for tuning the Drying Constant empirical model. Themore » second contains industrial drying data from the real operation of the dryer, and it is used for tuning the Residence Time empirical model. The experience from the industrial application of the simulator proved that the simulator is a powerful tool for flexible operation of an industrial dryer. This paper presents the total mathematical model of the dryer, the learning concept, and the databases, including useful information concerning the drying kinetics of bentonite. A simulator outline is presented and typical capabilities and uses are briefly described. A case study for flexible operation of an industrial dryer is discussed.« less
  • Fluidized bed and rotary dryers are two popular types of dryers utilized in almost every area of drying. In this study, both dryers are analyzed regarding their design and operational performance, so that they could be compared in a straightforward way. The mathematical models describing the convective drying process were evaluated for both types of dryers. Design procedures aiming at the determination of optimum sizing and operational characteristics for each type involved were carried out by appropriately optimizing the total annual cost of each structure for a given production capacity. Both dryer types were compared explicitly by evaluating optimum configurationsmore » for a wide range of production capacity values. Once the dryer sizing parameters are defined, its operational performance can be evaluated by comparing the optimum operational cost versus production capacity for predefined optimum designed structures. Rotary dryers turn out to be rather expensive compared to fluidized bed dryers, regarding design. On operational grounds, however, it is the other way around, due to the understandably favored heat transfer achieved in rotary dryers. Characteristic examples covering a wide range of materials--from food products to inorganic minerals--are included in order to demonstrate the performance of each process as well as the effectiveness of the proposed approach.« less