Development of an intelligent control system for wood drying processes

This paper presents the development of the intelligent adaptive control system of an industrial lumber drying process. The research project mainly focuses on automating the wood drying process through developing and implementing a closed-loop intelligent and adaptive controller with intelligent capability based on the moisture content of wood. The lumber drying process is complex due to many factors including distributed process dynamics, nonlinearities, drying property variation among wood pieces, and the coupling effects of temperature, relative humidity and moisture content. The developed control system involves the control of temperature at different zones, the control of ambient humidity, and the control of the moisture content in the lumber. The system model is developed using a system identification scheme based on the on-line input output data and knowledge accumulated through extensive lumber drying 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 on-line 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.