Experiment-based approach to reference trajectory tracking

This paper suggests an experiment-based approach to solve an optimal control problem that ensures reference trajectory tracking. The trajectory tracking problem is formulated in the framework of Iterative Learning Control and a new optimization algorithm is proposed. The optimization algorithm updates the reference input sequence on an entirely experiment-driven basis which accounts for operational constraints and employs an interior point barrier algorithm. A digitally simulated case study concerning a servo system is included in order to test the experiment-based approach and to highlight its advantages.