Passivity-Based Gain-Scheduled Control with Scheduling Matrices

TL;DR

This paper introduces a gain-scheduling control method using scheduling matrices for very strictly passive controllers, enhancing design flexibility and improving performance in uncertain robotic systems.

Contribution

It proposes a novel gain-scheduling approach with explicit conditions for passivity using scheduling matrices, extending beyond scalar signals.

Findings

Scheduling matrices improve closed-loop performance.

The method guarantees robust stability for uncertain robots.

Numerical simulations demonstrate enhanced control performance.

Abstract

This paper considers gain-scheduling of very strictly passive (VSP) subcontrollers using scheduling matrices. The use of scheduling matrices, over scalar scheduling signals, realizes greater design freedom, which in turn can improve closed-loop performance. The form and properties of the scheduling matrices such that the overall gain-scheduled controller is VSP are explicitly discussed. The proposed gain-scheduled VSP controller is used to control a rigid two-link robot subject to model uncertainty where robust input-output stability is assured via the passivity theorem. Numerical simulation results highlight the greater design freedom, resulting in improved performance, when scheduling matrices are used over scalar scheduled signals.