Erratum: Comparative performance study of QN and LM algorithms in predictive control for NNARX-identified model of hydro-power plant (Engineering with Computers 10.1007/s00366-006-0024-z);Comparative performance study of QN and LM algorithms in predictive control for NNARX-identified model of hydro-power plant

Engineering with Computers

Volumn 23, Issue 2, 2007, Pages 71-78

  Kishor, Nand ^b   Singh, S P ^a   Raghuvanshi, A S ^b   Sharma, P R ^b  

^a MOTILAL NEHRU NATIONAL INSTITUTE OF TECHNOLOGY   (India)

^b Royal Bhutan Institute of Technology   (Bhutan)

Author keywords

Cost function; Hydro plant; Identification; Neural network; Predictive control

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; COST FUNCTIONS; ITERATIVE METHODS; NEURAL NETWORKS; OPTIMIZATION; PREDICTIVE CONTROL SYSTEMS;

CONTROL COST FUNCTION (CCF); DYNAMIC PLANT MODEL; HYDRO-TURBINE; ITERATIVE ALGORITHMS;

HYDROELECTRIC POWER PLANTS;

EID: 34247567500     PISSN: 01770667     EISSN: 14355663     Source Type: Journal    
DOI: 10.1007/s00366-007-0055-0     Document Type: Erratum

References (21)

1. Cominos P, Munro N (2002) PID controllers: Recent tuning methods and design to specification. IEE Proc Control Theory Appl 149:46-53
2. Luqing YE, Shouping WEI, Zhaohui LI, Malik OP, Hope GS, Hancock GC (1990) An intelligent self-improving control strategy and its microprocessor-based implementation to a hydro-turbine governing system. Can J Electr Comput Eng 15:130-138
3. Zhaohui LI, Luqing YE, Shouping WEI, Malik OP, Hope GS, Hancock GC (1991) Field tests with a prototype duplicate microprocessor-based governor for a hydro-turbine. IEEE Trans EC 6:349-355
4. Zhaohui LI, Luqing YE, Shouping WEI, Malik OP, Hope GS, Hancock GC (1992) Fault tolerance aspects of a highly reliable microprocessor-based water turbine governor. IEEE Trans EC 7:1-7
5. Zhaohui LI, Malik OP (1997) An orthogonal test approach based control parameter optimization and its application to a hydro-turbine governor. IEEE Trans EC 12:388-393
6. Lansberry JE, Wozniak L (1992) Optimal hydro generator governor tuning with a genetic algorithm. IEEE Trans EC 7:623-630
7. Yamamoto T, Kanedam M, Oki T, Watanbe E, Tanaka K (1995) Intelligent tuning PID controllers. In: Proceedings of IEEE conference on intelligent systems for 21st century, 22-25 October 1995
8. Cheng Y, Ye L, Fu C, Cai W (2002) Anthropomorphic intelligent PID control and its application in hydro turbine governor. In: Proceedings of the first international conference on machine learning and cybernetics, Beijing, 4-5 November 2002
9. Xu F, Li Y, Qijuan C (1995) Study of the modeling of hydro turbine generating set. In: Proceedings of IEEE/IAS conference on industrial automation and control: Emerging technologies, 1995
10. Qijuan C, Zhihuai X (2000) Dynamic modeling of hydro turbine generating set. In: Proceedings of IEEE international conference on systems, man, and cybernetics, 2000
11. Chang J, Liu B, Cai W (1996) Nonlinear simulation of hydro turbine governing system based on neural network. In: Proceedings of IEEE international conference on systems, man, and cybernetics, 1996
12. Nørgaad M, Sørensen PH, Poulsen NK, Ravn O, Hansen LK (1996) Intelligent predictive control of nonlinear processes using neural networks. In: Proceedings of IEEE international symposium on intelligent control, 1996
13. Draeger A, Engell S, Ranke H (1995) Model predictive control using neural networks. IEEE Control Syst October 1995:61-66
14. IEEE Working Group (1992) Hydraulic turbine and turbine control models for system dynamic studies. IEEE Trans PAS 7:167-179
15. Quiroga OD (2000) Modelling and nonlinear control of voltage frequency of hydroelectric power plants. Universidad Politècnica De Cataluña, Spain
16. Narendra KS, Parthasarathy K (1990) Identification and control of dynamical systems using neural networks. IEEE Trans Neural Netw 1:4-27
17. Cybenko G (1989) Approximations by superpositions of a sigmoidal function. Math Control Signals Syst 2:303-314
18. Funahashi K (1989) On the approximate realization of continuous mappings by neural networks. Neural Netw 2:183-192
19. Nørgaad M. (2000) Neural network based system identification toolbox. Technical report 00-E-891, 2000. Department of Automation, Technical University of Denmark
20. Constantin N (2003) Adaptive neural predictive techniques for nonlinear control. Stud Inf Control 12:285-291
21. Norgaard M, Ravn O, Poulsen NK, Hansen LK (2000) Neural networks for modeling and control of dynamics systems. Springer, Berlin Heidelberg New York