Robust Admittance Control for Human Arm Strength Augmentation With Guaranteed Passivity: A Complementary Design
Wulin Zou, Xiang Chen, Shilei Li, Pu Duan, Ningbo Yu, Ling Shi
Abstract
For the position-error feedback-based admittance control in human strength augmentation, there are inherent conflicts among different performances, such as accuracy, passivity, and robustness. In this article, we propose a multi-objective complementary control framework that enables decoupled nominal admittance performance and robustness while preserving the passivity. Essentially, the framework consists of three parts. An linear-quadratic-gaussian (LQG) controller and a feedforward controller, which jointly render the nominally accurate and passive admittance performance against noise, and a robust regulator, which recovers the nominal performance when disturbance and/or uncertainty exist. The efficacy of the proposed method is verified on a human arm strength augmentation device for load lifting. Compelling simulations, experiments, and comparison results demonstrate the efficacy and superiority of the proposed method.