A norm optimal iterative learning control based train trajectory tracking approach
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AbstractA 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.
CitationSun, 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.3966-3971
TypeConference papers, meetings and proceedings