Abstract
This paper analyzes the parking process of maglev trains, establishes the corresponding mathematical model, based on the method of terminal iterative learning control(TILC), uses the stopping position error in the previous braking process to update the current control curve. In this paper, we select the initial braking position, initial speed or braking force or a combination thereof as the control input, and formulate the corresponding learning law. Finally, a line is simulated, and the traditional TILC method and the optimal TILC method are compared through simulation experiments, which verify that the latter has a faster convergence speed.
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