A study on the higher order learning control algorithm

Abstract EN

Learning control is a new approach to the problem of improving transient response over fixed time duration by iterative training.

It is a recursive on line control method that relies on less calculation and requires less a priori knowledge about the system dynamics.

It can be used as a real time control method for complex systems such as robot manipulators.

In this paper the proposed algorithm is used for improving the performance at the next trail on the basis of more than one past error history contained in the trajectories generated at prior iterations.

A convergence proof is given and examples are provided to show the effectiveness of the algorithm.