会议专题

Neural Network Based Robust Variable Structure Control of Wood Drying Kiln

Proper control of the wood-drying kiln is crucial to ensure the satisfactory quality of dried wood and in minimizing drying time and energy. This paper investigates the development and evaluation of a robust control system for a wood drying kiln process incorporating variable structure control (VSC) such that the moisture content of lumber will reach and be stabilized at the desired set point. A description of the dynamics of the wood drying process by means of the time-delay neural network is also presented, in which the back-propagation algorithm was implemented for testing, training and validation. Then this identified model is used for simulation purpose and controller design. For comparison purpose, a conventional proportional-integral-derivative (PID) controller is also employed and system performance is evaluated through simulations. The results are evaluated to tune the controller parameters to achieve good performance in the wood-drying kiln and the VSC strategy promises improved performance. The control system developed in this study may be applied in industrial wood-drying kilns, with a clear potential for improved quality and increased speed of drying.

Wood Drying Kiln Variable Structure Control Temperature Moisture Control Intelligent Control

Qinglei Hu Jun Cao Liping Sun Yaqiu Liu

School of Electromechanical Engineering,Northeast Forestry University,Harbin,150040,China;Department School of Electromechanical Engineering,Northeast Forestry University,Harbin,150040,China

国际会议

2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

广西桂林

英文

4828-4833

2009-06-17(万方平台首次上网日期,不代表论文的发表时间)