Discrete learning control for robots using partial model knowledge

The authors describe an iterative learning controller for robot manipulators. The learning control method presented makes use of partial model knowledge of the robot system and systematically merges desirable types of sensor data for iterative control. Fast convergence can always be obtained without going through complicated tuning exercises. The experimental results showed the superior learning performance of the robot system working with the learning controller