Decentralized Neural Network Variable Structure Controller Design for Wood Drying Process
This paper investigates the development and evaluation of a robust control system for a wood drying kiln process incorporating decentralized variable structure control (DVSC) 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 DVSC 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 Decentralized Neural Variable Structure Control Temperature-Moisture Control
Jun Cao Liangkuan Zhu Qinglei Hu
School of Electromechanical Engineering, Northeast Forestry University, Harbin, 150040 School of Electromechanical Engineering, Northeast Forestry University, Harbin, 150040 Harbin Instit
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
506-511
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）