A novel iterative learning control method for longitudinal trajectory tracking of aerospace vehicles

Abstract Considering the precise model information of aerospace is not always available under effect external disturbance and uncertainty, a new data‐driven point‐to‐point iterative learning control (PTPILC) method proposed for vehicles to track predetermined trajectory. Firstly, system vehicle converted into discrete form without any omission, which reflects dynamics original by input output data. Then, objective function tracking error in quadratic facilitate application conjugate gradient algorithm, develops an improved PTPILC method. And convergence analysis presented. Furthermore, parameters are optimized make more robust against different parameter deviations. Finally, effectiveness illustrated simulations.