Intelligent reconfigurable control of robot manipulators

Abstract

One approach towards improving the reliability of high-performance robotic systems is to allow for the automatic reconfiguration of the robot's control system to accommodate actuator failure and/or damage. The new concept of the extended plant and its identification in closed loop is introduced for developing a reconfigurable robot manipulator controller. It is made possible through the use of artificial neural networks. A simulation study demonstrates the effectiveness of the developed control algorithm.