Ricerc@Sapienza

This paper develops a control strategy for a life-support device to be attached to an orbiting satellite to extend its operational life. The objective is met in such a way that the original satellite keeps operating without communications between the two systems (also valuable for energy efficiency). The case in which the original satellite is equipped with a feedback-linearization based controller is considered and the control law for the life-support is developed with the same methodology, obtaining a compensating control which recovers the performance of the original control strategy.

Feedback Linearization (FL) allows the best control performance in executing a desired motion task when an accurate dynamic model of a fully actuated robot is available. However, due to residual parametric uncertainties and unmodeled dynamic effects, a complete cancellation of the nonlinear dynamics by feedback is hardly achieved in practice. In this paper, we summarize a novel learning framework aimed at improving online the torque correction necessary for obtaining perfect cancellation with a FL controller, using only joint position measurements.

The concept of partially minimum phase systems is introduced and used with reference to the class of nonlinear systems exhibiting a linear output. It turns out that input-output feedback linearization with stability of the internal dynamics can be pursued via the use of a dummy output with respect to which the system is minimum-phase. The design strategy is extended to multirate sampled-data control and a working example illustrates the performances.