TY - GEN
T1 - Adaptive neural network control of helicopters with unknown dynamics
AU - Ge, Shuzhi Sam
AU - Ren, Beibei
AU - Tee, Keng Peng
PY - 2006
Y1 - 2006
N2 - In this paper, adaptive neural network (NN) tracking control is considered for helicopters in the presence of parametric and functional uncertainties. Based on Lyapunov synthesis, the proposed adaptive NN control ensures that the system outputs track the given bounded reference signals to a small neighborhood of zero, and guarantees semiglobal uniformly ultimate boundedness (SGUUB) of all the closed-loop signals. The effectiveness of the proposed control is illustrated through extensive simulations.
AB - In this paper, adaptive neural network (NN) tracking control is considered for helicopters in the presence of parametric and functional uncertainties. Based on Lyapunov synthesis, the proposed adaptive NN control ensures that the system outputs track the given bounded reference signals to a small neighborhood of zero, and guarantees semiglobal uniformly ultimate boundedness (SGUUB) of all the closed-loop signals. The effectiveness of the proposed control is illustrated through extensive simulations.
UR - http://www.scopus.com/inward/record.url?scp=39649085151&partnerID=8YFLogxK
U2 - 10.1109/cdc.2006.377693
DO - 10.1109/cdc.2006.377693
M3 - Conference contribution
AN - SCOPUS:39649085151
SN - 1424401712
SN - 9781424401710
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 3022
EP - 3027
BT - Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 45th IEEE Conference on Decision and Control 2006, CDC
Y2 - 13 December 2006 through 15 December 2006
ER -