Learning control of an overhead crane for obstacle avoidance

A control strategy is presented for a 3-dimensional overhead crane. Using the differential flatness of the crane and a parametrization method, we calculate the optimal trajectory of the payload that results in minimum transfer time when there exist obstacles in the direct moving path. A learning algorithm is then used to generate the desired feedforward input signal that can drive the system output to track the optimal trajectory exactly.