Title :
Robust spacecraft attitude control using fuzzy CMAC
Author :
Kwan, C.M. ; Xu, H. ; Lewis, F.L. ; Haynes, L. ; Pryor, J.D.
Author_Institution :
Intelligent Autom. Inc., Rockville, MD, USA
Abstract :
In this paper, we propose to use a new neural network called fuzzy CMAC (cerebellar model arithmetic computer) to tackle the attitude control problem. The advantages are no linearity in the system parameter assumption is needed and no upper bounds of unknown parameters is required. An online tuning scheme with no off-line training phase is used to update the weights in the neural network. Attitude tracking errors are guaranteed to be bounded
Keywords :
aerospace control; attitude control; cerebellar model arithmetic computers; fuzzy control; fuzzy neural nets; neurocontrollers; robust control; space vehicles; attitude tracking errors; fuzzy CMAC; neural network; online tuning scheme; robust spacecraft attitude control; weight updating; Computer errors; Computer networks; Digital arithmetic; Fuzzy control; Fuzzy neural networks; Linearity; Neural networks; Robust control; Space vehicles; Upper bound;
Conference_Titel :
Intelligent Control, 1996., Proceedings of the 1996 IEEE International Symposium on
Conference_Location :
Dearborn, MI
Print_ISBN :
0-7803-2978-3
DOI :
10.1109/ISIC.1996.556175
