A norm optimal iterative learning control based train trajectory tracking approach
Abstract
A norm optimal iterative learning control (NOILC) is proposed and applied in train trajectory tracking problem, and it then is extended to the cases with traction/braking constraint. Rigorous theoretical analysis has shown that the proposed approach can guarantee the asymptotic convergence of train speed and position to desired profiles as iteration number goes infinity. Simulation results further demonstrate the effectiveness of the proposed NOILC approach.Citation
Sun, H., Hou, Z. and Li, D. (2012) 'A norm optimal iterative learning control based train trajectory tracking approach', Decision and Control (CDC), IEEE 51st Annual Conference on, pp.3966-3971Type
Conference papers, meetings and proceedingsLanguage
enae974a485f413a2113503eed53cd6c53
10.1109/CDC.2012.6426487