Title :
Application of a neural network controller to a process
Author :
Min, Lim Choo ; Qing, Li
Author_Institution :
Dept. of Electron. & Comput. Eng., Ngee Ann Polytech., Singapore
Abstract :
A neural network control strategy is proposed to compensate for any variations in the parameters and disturbance of a first-order process. The advantages of this approach are that only the estimated plant parameters are required and the neural network is trained online. As such, the overall system is robust even in the presence of large variations in the plant parameters. The effectiveness of this controller is demonstrated using digital simulation studies
Keywords :
closed loop systems; control system synthesis; learning (artificial intelligence); neurocontrollers; process control; real-time systems; closed loop systems; first-order process; neural network; neurocontroller; online learning; process control; Application software; Computer networks; Control systems; Digital simulation; Equations; Error correction; Neural networks; Process control; Robustness; System performance;
Conference_Titel :
Industrial Technology, 1996. (ICIT '96), Proceedings of The IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
0-7803-3104-4
DOI :
10.1109/ICIT.1996.601687
