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UBC Theses and Dissertations

Experimental modeling and intelligent control of a wood-drying kiln Yan, Givon Chuen Kee


This thesis focuses on the development, implementation, and evaluation of a control system for a lumber drying kiln process. The control system uses sensory feedback from the moisture content sensors of the wood pieces and from the temperature sensors of the kiln interior. Both conventional and fuzzy-logic proportional-integral-derivative control are developed. In order to achieve the research goals, this investigation is divided into two parts. The first part of the thesis consists of the system modeling and validation where experimental modeling is emphasized. The second part presents the controller design, development, and implementation. Both simulation studies and experimental studies on a prototype wood-drying kiln are carried out. System modeling is performed by system identification scheme using experimental data and recursive least squares algorithm for parameter estimation. Process models are developed based on the assumptions that the process is a linear, time invariant, and single-input-single-output (SISO) uncoupled one with no time delay. Two different approaches are utilized in constructing the system model. The first approach is to obtain the system model directly as a single model structure, while the second approach is to obtain the system model through separating the overall system into two subsystems. Models are built assuming different dynamic orders and then validated by comparing the model response with the actual kiln response, based on experimental data. Extensive computer simulations are carried out to investigate the validity of the dynamic models. Results illustrate nonlinear, time-varying, and time delay characteristics of the process. In the context of controller design and development, two different control methodologies are developed: a conventional proportional-integral-derivative (PID) controller and a direct fuzzy logic controller (FLC). Simulations are performed using the model developed through system identification. System performance is evaluated through simulations performed using Matlab Simulink. The developed control system is then implemented in a downscaled industrial kiln which is located at the Innovation Centre of National Research Council (NRC) of Canada. This experimental setup is equipped with a variety of sensors, which include thermocouples for temperature feedback, an air velocity transmitter for measuring airflow speed in the plenum, relative humidity sensors for measuring the relative humidity inside the kiln, and wood moisture content sensors for measuring the moisture content of the wood pieces. The actuators of the experimental kiln system include an on/off electric heater and a variable-speed fan. All communications between actuators, sensors, and controllers are supported by software programming developed in Delphi, and located with the control computer. Extensive experimental studies are carried out on-line using the two controllers, and the results are evaluated to tune the controller parameters for achieving good performance in the wood drying kiln. The control system developed in this research may be applied in industrial wood drying kilns, with a clear potential for improved quality and increased speed of drying.

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