Comparison between human supervisory control and hierarchical control system based on human's knowledge in petroleum plant

Presents a hierarchical control system which is designed based on a human's knowledge, which is a supervisor of conventional PID controllers. The hierarchical control system consists of two control function blocks, where we use (1) a statistical model using multi-regression analysis for the function block to estimate parameters of plant operation and (2) fuzzy logic for the control function block to compensate operating conditions. The hierarchical control system has been applied to hydrogen purity controls in a large scale petroleum refining plant and verified that the control system has shown better performance than human supervisory control. The human supervisor is necessary only when the system structure changes in the hierarchical system.

[1]  Motohide Umano,et al.  Neuro-fuzzy hybrid control system of nonlinear process in petroleum plant , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[2]  K. Shida,et al.  MRFACS with nonlinear consequents by fuzzy identification of system for time delay system , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[3]  Shaohua Tan,et al.  PID self-tuning control using a fuzzy adaptive mechanism , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[4]  Kazuo Tanaka,et al.  Application of practical fuzzy-PID hybrid control system to petrochemical plant , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[5]  L. Zheng,et al.  A practical guide to tune of proportional and integral (PI) like fuzzy controllers , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[6]  Tetsuji Tani,et al.  A Design Method of Fuzzy-PID Combination Control System and Its Application to Heater Outlet Temperature Control , 1991 .

[7]  W. Pedrycz,et al.  A design method for a class of fuzzy hierarchical controllers , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[8]  Shigeyasu Kawaji,et al.  Fuzzy hybrid control of DC servomotor , 1991 .