Neural PID decoupling control of air cushion headbox based on genetic algorithms

Author

Zhou, Keliang ; Chen, Pengzhen

Author_Institution

Sch. of Mech. & Electr. Eng., Jiangxi Univ. of Sci. & Technol., Ganzhou, China

fYear

2011

fDate

8-10 Aug. 2011

Firstpage

4099

Lastpage

4102

Abstract

For the total pressure and slurry level are nonlinear and coupled in the air headbox, through the use of genetic algorithm to optimize PID neural network weights to achieve the P, I, D the best combination to complete the total headbox flow Pressure and slurry level decoupling control. Finally, the MATLAB simulation shows that the method has high control accuracy, fast dynamic response, the use of high value features.

Keywords

dynamic response; forming processes; genetic algorithms; neurocontrollers; paper making; paper making machines; pressure control; sheet materials; slurries; three-term control; MATLAB simulation; PID neural network; air cushion headbox; dynamic response; genetic algorithm; neural PID decoupling control; paper machinery; sheet forming; slurry level decoupling control; total pressure level; Biological neural networks; Control systems; Couplings; Genetic algorithms; Neurons; Optimization; Slurries; PIDneural network; decoupling control; genetic algorithms; headboxt;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on

Conference_Location

Deng Leng

Print_ISBN

978-1-4577-0535-9

Type

conf

DOI

10.1109/AIMSEC.2011.6009951

Filename

6009951