Title :
MMSE Controller Design Based on RBF Neural Network
Author :
Yu, Jianli ; Zhang, Zongwei ; Xu, Liang
Author_Institution :
Sch. of Electr. & Inf. Eng., Zhongyuan Univ. of Technol., Zhengzhou, China
Abstract :
A minimum mean squared error (MMSE) controller based on RBF neural network has been developed as a new EPC strategy used in an integrated SPC and EPC system for process adjusting and monitoring. The application example used in chemical production process which is an AR(2) model shows that method can effectively reduce the process variations, then SPC control charts have been used to monitor the process output after adjustment. The control charts of the output reveal the RBF network based MMSE controller as the EPC strategy is an ideal control method as compared with the traditional MMSE control.
Keywords :
control charts; control system synthesis; least mean squares methods; numerical control; process monitoring; radial basis function networks; statistical process control; EPC strategy; MMSE controller design; RBF neural network; SPC control chart; chemical production process; integrated SPC; minimum mean squared error; process adjusting; process monitoring; statistical process control; Automatic control; Chemical processes; Chemical products; Computer networks; Control charts; Control systems; Feedforward neural networks; Neural networks; Process control; Production; EPC; MMSE control; RBF neural network; SPC;
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Print_ISBN :
978-0-7695-3804-4
DOI :
10.1109/ICICTA.2009.27
