228 publications from this institution
This paper presents a new damping control scheme for piezo-actuated nanopositioning stages with recursive delayed position feedback (RDPF). The RDPF is proposed to attenuate the resonant mode of the nanopositioning stage in the inner feedback loop, which results in a neutral-type time-delay system. To realize the pole placement of this system, a new numerical integration method is proposed to determine the rightmost pole and select the parameters of the RDPF. Then, a high-gain proportional-integral (PI) controller is designed in the outer loop to minimize the tracking errors caused by the hysteresis nonlinearity and modeling uncertainties. To validate the effectiveness of the proposed approach, comparative experiments are conducted on a piezo-actuated nanopositioning stage. Experimental results demonstrate that the proposed approach improves the control bandwidth of the system from 32.5 Hz (with the PI controller) and 687 Hz (with the conventional delayed position feedback based controller) to 793 Hz.
Fabric-based soft gloves, due to their safety, light weight, and compliance, exhibit promising potential in assisting individuals with hand impairments. However, most existing soft gloves focus solely on finger flexion and extension, with limited consideration for thumb assistance. This restricts their effectiveness in tasks requiring extensive workspace and dexterous manipulation. In this work, we present a new class of fabric-based soft glove with 15 degrees of freedom (DOFs), including finger flexion/extension, thumb abduction/adduction, thumb opposition/reposition, and finger abduction. The high-DOF fabric-based soft glove integrates bidirectional fabric-based pneumatic actuators (FPAs) for finger flexion/extension, X-crossing pneumatic artificial muscles (X-PAMs) for thumb assistance, and Y-shaped bladed FPAs for finger abduction. To enhance the thumb tip workspace, we optimize the X-PAM positioning by modeling thumb kinematics from an anatomical perspective. The experimental results show that the optimized passive workspace of the thumb, assisted by the glove, encompasses approximately 70% of its active workspace. Through our mirror control system, we further demonstrate the glove's capability to perform complex gestures and versatile grasping tasks with various object geometries, sizes (0.1-11.5 cm), and masses (1.7-500.0 g). The glove supports both power and precision grasps, as well as fine manipulations.
