Artificial Intelligence Review - Special issue on lazy learning
Locally Weighted Learning for Control
Artificial Intelligence Review - Special issue on lazy learning
Optimal multi-step k-nearest neighbor search
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Direct learning of control efforts for trajectories with different magnitude scales
Automatica (Journal of IFAC)
Generalization of Iterative Learning Control for Multiple Desired Trajectories in Robotic Systems
PRICAI '02 Proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Brief paper: Experience inclusion in iterative learning controllers: Fuzzy model based approaches
Engineering Applications of Artificial Intelligence
Hi-index | 22.14 |
A method of incorporating experience in iterative learning controllers is proposed in this paper. Importance of the selection of initial control input in the convergence of error is highlighted. It is proposed that if previous experience of the controller can be incorporated in the selection of the initial control input for a new desired trajectory tracking task, the convergence of error can be improved without modifying the structure of the controller. Therefore, the proposed method is very general and is applicable to most of the iterative learning control algorithms.