An adaptive control strategy for robotic cutting

Abstract

Automation of a cutting process requires a system that is able to perform a planned cutting work irrespective of the interaction forces experienced during this process. For a robotic cutter the controller must adjust the applied force exerted on the material to be cut, while complying with unknown environment restrictions and disturbances. In this paper the problem of cutting a media by a blade is investigated. Based on a learning philosophy and position and velocity errors feedback an algorithm for the control of such a process is presented. An adaptive position controller and a switching logical velocity controller ensure the cutting operation is performed along a desired path with a desired velocity, while a learning control strategy is employed to adjust the required cutting force. The latter is a force learning algorithm which uses the force feedback. The effectiveness of the presented control system is demonstrated by simulation results.