Computationally efficient predictive adaptive control for robot control in dynamic environments and task domains

This paper presents the tuning and implementation of a computationally efficient adaptive predictive control algorithm for robotic utility. The controller addresses the need for practical, computationally efficient, robust real-time adaptive control for multivariable robotic systems. It exploits a special matrix representation to obtain substantial reductions in the computational expense relative to standard methods. We report the design, modeling, and implementation of the controller on a simple pick-and-place manipulator and on an industrial robot loading heavy shells within the magazine of a naval vessel. The proposed controller demonstrates the ability to adapt to varying actuator performance and rapidly changing sea states. Future work involves the implementation and testing of the controller during actual naval operations. We believe this work may serve as a foundation to address control issues for robots working in uncertain dynamic environments and provide a basis for design and control of shipboard robotic devices.