Title :
Adaptive NN control of dynamic systems with unknown dynamic friction
Author :
Ge, S.S. ; Lee, T.H. ; Wang, J.
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
Abstract :
Based on the dynamic LuGre friction model, adaptive NN controllers are presented by using neural networks to parameterize the unknown characteristic function α(x, x˙) or the unknown dynamic friction bounding function respectively. Using Lyapunov synthesis, the adaptive control algorithms are designed to achieve globally asymptotic tracking of the desired trajectory and guarantee the boundedness of all the signals in the closed-loop. Intensive simulations are carried out to verify the effectiveness of the proposed methods
Keywords :
Lyapunov methods; adaptive control; closed loop systems; control system synthesis; friction; motion control; neurocontrollers; observers; robust control; servomechanisms; Lyapunov synthesis; adaptive neural net control; dynamic LuGre friction model; dynamic systems; globally asymptotic tracking; unknown characteristic function; unknown dynamic friction; Adaptive control; Algorithm design and analysis; Control system synthesis; Control systems; Friction; Network synthesis; Neural networks; Programmable control; Signal design; Signal synthesis;
Conference_Titel :
Decision and Control, 2000. Proceedings of the 39th IEEE Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
0-7803-6638-7
DOI :
10.1109/CDC.2000.912116
