Title :
The design of neural network controller for nonlinear plants
Author :
Yingkai, Zhao ; Jinguo, Lin ; Zhibing, Shu
Author_Institution :
Nanjing Univ. of Chem. Technol., China
Abstract :
For the further development of the APC algorithm for DCS (distributed control system), the design of a neural network controller for nonlinear plants is discussed. First, a neural network model is obtained for the nonlinear plants. Next, the GPC algorithm based on the linearized model is used to synthesize a linear controller for each operating point. Finally, the neural net controller is trained as a nonlinear controller. The simulation of PH process control proves the effective of this control algorithm
Keywords :
control system synthesis; distributed control; linear systems; neurocontrollers; nonlinear control systems; pH control; process control; APC algorithm; DCS; GPC algorithm; PH process control; backpropagation; distributed control system; generalized predictive control; linear controller; neural network controller design; neural network model; nonlinear plants; simulation; training; Algorithm design and analysis; Chemical technology; Control system synthesis; Control systems; Costs; Distributed control; Network synthesis; Neural networks; Predictive control; Process control;
Conference_Titel :
Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4253-4
DOI :
10.1109/ICIPS.1997.672838
