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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 knowledgebase 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 directin-wood moisture measurement .