Study on multiple models predictive control for superheated steam temperature based on local neural network models

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering

Volumn 24, Issue 8, 2004, Pages 190-195

  Luan, Xiu Chun ^a   Li, Shi Yong ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Local model; Multiple models; Neural network; Predictive control; Superheated steam temperature; Thermal power engineering

Indexed keywords

BOILERS; CASCADE CONTROL SYSTEMS; DESIGN; NEURAL NETWORKS; PREDICTIVE CONTROL SYSTEMS; SIMULATION; TEMPERATURE;

LOCAL MODEL; MULTIPLE MODEL; PREDICTIVE CONTROL; SUPERHEATED STEAM TEMPERATURE;

STEAM;

EID: 4644230065     PISSN: 02588013     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (22)

1. Lu Jianhong, Chen Laijiu. The prospects of premonitory control in thermal controlling [J]. Power Engineering, 1997, 17(2): 12-15
2. Hunt K J, Sbarbaro D, Zbikowski R, et al Neural networks for control systems - a survey [J]. Automatica, 1992, 28(6): 1083-1112
3. Soloway D, Haley P J. Neural generalized predictive control [A]. Proceedings of the 1996 IEEE International Symposium on Intelligent Control [C]. Dearborn, MI, USA, 15-18 Sep 1996: 277-282.
4. Lazar Mirceaa, Pastravanu Octaviana. A neural predictive controller for non-linear systems [J]. Mathematics and Computers in Simulation. 2002, 60(3-5): 315-324.
5. A physical law and neural network integrated modeling method for boiler superheater systems [J]. Proceedings of the CSEE, 2001, 21(1): 73-76.
6. Wang Guangjun, He Zuwei, Chen Hong, Boiler evaporation system simulation based on neural network and process mechanism characteristic [J]. Proceedings of the CSEE, 2001, 21(11): 65-68.
7. Wang Guangjun, He Zuwei, Chen Hong, Dynamic simulation of the superheat system of boiler based on neural network and process mechanism [J]. Proceedings of the CSEE, 2001, 21(12): 38-40.
8. Liu Zhiyuan, Lu Jianhong, Chen Laijiu. A novel RBF neural network and its application in thermal processes modelling [J]. Proceedings of the CSEE, 2002, 22(9): 118-122.
9. Johansen T A, Foss B A. Identification of non-linear system structure and parameters using regime decomposition [J]. Automatica, 1995, 31(2): 321-326.
10. Anass Boukhris, Gilles Mourot, Jose Ragot. Non-linear dynamic system identification: a multi-model approach [J]. International Journal of Control, 1999, 72(7/8): 591-604.
11. Fan Yongsheng, Xu Zhigao, Chen Laijiu. Study of adaptive fuzzy control of boiler superheated steam temperature based on dynamic mechanism analysis [J]. Proceedings of the CSEE, 1997, 17(1): 23-28.
12. Clarke D W, Mohtadi C, Tuffs P S. Generalized predictive control [J]. Automatica, 1987, 23(2): 137-160
13. Nørgaard M, Ravn O, Poulsen N K, et al. Neural networks for modeling and control of dynamic systems: a practitioner's handbook [M]. London: Springer-Verlag London Limited, 2000.
14. Chen S, Billings S A, Grant P M. Non-linear system identification using neural networks [J]. International Journal of Control, 1990, 51(6): 1191-1214.
15. Leontaritis I J, Bilhngs S A. Input-output parametric models for non-linear systems [J]. International Journal of Control, 1987, 41(2): 303-344.
16. Chen S, Billings S A. Representations of non-linear systems: the NARMAX model [J]. International Journal of Control, 1989, 49(3): 1013-1032.
17. Badr A, Binder Z, Rey D. Weighted multi-model control [J]. International Journal of Systems Science, 1992, 23(1): 145-149.