Modeling and Preview $H_\infty$ Control Design for Motion Control of Elastic-Joint Robots With Uncertainties

This paper describes a novel approach combining identification and control design for motion control of multiple-link elastic-joint robots with motor sensors only and in presence of model uncertainties. The proposed model-based control design method makes use of the H
_∞
(H-infinity) framework to design a two-degree-of-freedom controller with anticipation able both to 1) withstand uncertainties or variations in model parameters and 2) follow reference trajectories with prescribed precision thanks to a preview feedforward action which anticipates the future trajectory on a given time horizon. The proposed design methodology is experimentally evaluated on a two-degree-of-freedom lightweight robotic arm, which is first modeled and identified in the frequency domain. Experimental validation of the controller confirms that the objectives of the dynamic precision in trajectory tracking and tip vibration damping are both achieved. Additional analysis and numerical simulations illustrate how the presented preview H
_∞
controller may be seen as an extension, with supplementary design parameters, of the traditional motor feedback with compensations based on the robot inverse dynamic model. A performance comparison between the proposed control method and the traditional inversion-based control shows the benefits of the anticipatory action and the possibilities offered by an H
_∞
design framework for the management of tradeoffs in the specifications.