Iterative learning identification applied to automated off-highway vehicle

This brief presents an approach for identifying the lateral dynamics of an automated off-highway agricultural vehicle for the purpose of automatic steering controller design. A second-order model is proposed to represent the vehicle lateral dynamics. An iterative learning identification (ILI) method is used to identify the model parameters. Simulation and experimental results under various test conditions show parameter convergence. The ILI results are compared with a gradient-based adaptive parameter estimation approach. The results highlight the practical benefit of the ILI approach for systems with repeated trajectories.