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On the design of a neural network autolander
Author(s) -
Cox C.,
Stepniewski S.,
Jorgensen C.,
Saeks R.,
Lewis C.
Publication year - 1999
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/(sici)1099-1239(19991215)9:14<1071::aid-rnc453>3.0.co;2-w
Subject(s) - artificial neural network , computer science , quadratic equation , levenberg–marquardt algorithm , stability (learning theory) , control engineering , control theory (sociology) , algorithm , mathematical optimization , artificial intelligence , engineering , machine learning , mathematics , geometry , control (management)
A research program directed at the development of an autolander for NASA's X‐33 prototype reusable launch vehicle is described. The autolander is based on a new linear quadratic adaptive critic algorithm. It is implemented by an array of Functional Link neural networks and is trained by a modified Levenberg–Marquardt method. A full stability theory is developed for the new adaptive critic algorithm. Simulation results are presented for the linear–quadratic case. Copyright © 1999 John Wiley & Sons, Ltd.