Optimum gain-scheduling PID controllers for gas turbine engines based on NARMAX and neural network models

American Society of Mechanical Engineers, International Gas Turbine Institute, Turbo Expo (Publication) IGTI

Volumn 1, Issue , 2003, Pages 509-515

  Mu, Junxia ^a   Rees, David ^a   Chiras, Neophytos ^b  

^a UNIVERSITY OF GLAMORGAN   (United Kingdom)

^b Praxis Critical Systems   (United Kingdom)

Author keywords

Feedforward neural network models; Gain scheduling PID controllers; Gas turbines; NARMAX models

Indexed keywords

FUEL FLOW; GAIN-SCHEDULING CONTROL;

AEROSPACE APPLICATIONS; ERROR ANALYSIS; GAIN MEASUREMENT; GAS TURBINES; NONLINEAR EQUATIONS; ROBUSTNESS (CONTROL SYSTEMS); SHAFTS (MACHINE COMPONENTS);

FEEDFORWARD NEURAL NETWORKS;

EID: 0346317315     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1115/GT2003-38667     Document Type: Conference Paper

References (13)

1. Dadd G. J., Sutton A. E. and Greig A. W. M., 1996, "Multivariable control of military engines," AGARD conference proceedings No. 572 - Advanced Aero-Engine Concepts and Controls, paper 28: 1-12.
2. Evans C., Rees D. and Hill D., 1998, "Frequency-domain identification of gas turbine dynamics," IEEE Transactions on Control Systems Technology, 6, 5, pp. 651-662.
3. Evans C., Borrell A. and Rees D., 1999, "Testing and modeling gas turbines using multisine signals and frequency-domain techniques," ASME Journal of Engineering for Gas Turbine and Power, 121, pp. 451-457.
4. Evans C., Rees D. and Borrell A., 2000, "Identification of aircraft gas turbine dynamics using frequency-domain techniques," Control Engineering Practice, 8, 4, pp. 457-467.
5. Chiras N., Evans C. and Rees D., 2002, "Global nonlinear modeling of gas turbine dynamics using NARMAX structures," ASME Journal of Engineering and Power, vol. 124, no. 4, pp. 817-826.
6. Chiras N., Evans C and Rees D., 2002, "Nonlinear gas turbine modeling using feedforward neural networks," ASME Turbo Expo' 2002 congress, Amsterdam, Netherlands, GT-2002-30035.
7. Chiras N., Evans C, Rees D., 2001, "Nonlinear gas turbine modeling: A comparison of NARMAX and neural network approaches," Advances in Process Control, 6, York, pp. 71-80.
8. Åström K. J., Häglund T., 2001, "The future of PID control," Control Engineering Practice, 9, pp. 1163-1175.
9. th Asian Control Conference, Singapore, WM9-24, pp. 826-832.
10. Billings S. A., Chen S. and M. J. Korenberg, 1989, "Identification of MIMO nonlinear systems using a forward-regression orthogonal estimator, " Int. J. Control, 49, 6, pp. 2157-2189.
11. Cybenco G., 1989, "Approximation by superpositions of a sigmoidal function," Mathematics of Control, Signals and System, 2, 4, pp. 303-314.
12. Nørgaard M., 2000, "Neural Network Based System Identification Toolbox," Tech. Report. 00-E-891, Department of Automation, Technical University of Denmark.
13. Grace A., 1996, "Optimization Toolbox for Use with MATLAB," The Mathworks Inc.