Interaction control of an industrial manipulator using LPV techniques

• An LPV gain-scheduling technique is used to interaction control of a 6DOF manipulator.
• A way is proposed to investigate the coupling between submodels of a manipulator.
• LPV and inverse dynamics controllers are used to position control of two submodels.
• The position controllers are combined with a force controller in a hybrid structure.
• The proposed control structure outperformes a pure inverse dynamics controller.

This paper presents the design and implementation of a hybrid force/motion control scheme on a six-degrees-of-freedom robotic manipulator employing a gain-scheduled linear parameter-varying (LPV) controller. A nonlinear dynamic model of the manipulator is obtained and the unknown parameters are estimated. The manipulator is decomposed into an inner and a wrist submodel, and a practical way is proposed to investigate the coupling between them. The motion control part of the hybrid controller which is the main focus of this paper is formed by a combination of an LPV controller and a model-based inverse dynamics controller for the inner submodel and the wrist joints, respectively. A quasi-LPV model with a reduced number of scheduling parameters is derived for the inner submodel, and a polytopic LPV gain-scheduled controller is synthesized in a two-degrees-of-freedom structure including feedback and feedforward parts, which is augmented by a friction compensation term. A PD controller with a feedforward path is designed to control the interaction force. The proposed hybrid force/motion scheme is implemented on the 6-DOF CRS A465 robotic manipulator to perform a writing task. Comparison of the results with those of a hybrid force/motion controller with a plain model-based inverse dynamics motion control and the same force control shows that the proposed controller improves the position tracking performance significantly.