Development of an intelligent control system for wood drying processes

Presents the development of the intelligent adaptive control of industrial lumber drying. The project focuses on a closed-loop intelligent and adaptive controller based on the moisture content of wood. The drying process is complex due to many factors including distributed process dynamics, nonlinearities, drying property variations, and the coupling effects of temperature, relative humidity and moisture content. The developed control system involves the control of temperature at different zones, of ambient humidity, and of the moisture content in the lumber. The system model is developed using a system identification scheme based on the online input/output data and knowledge accumulated through extensive tests. The knowledge base of the fuzzy tuner is derived from the drying schedule for a specific wood specimen. The indirect fuzzy adaptive controller design incorporates adaptive control based on local drying dynamics and intelligence reflecting process dynamics relating to species, size and other conditions of lumber. This paper also presents results of simulation and online implementation of a closed-loop intelligent controller for wood moisture control using fuzzy logic based on direct in-wood moisture measurement. The results show that the proposed approach for overall control has a great potential for performance improvement when applied to other industrial kilns. A conventional adaptive controller is implemented as well, and its performance is compared with that of the fuzzy logic adaptive controller.