Date of Award
5-2026
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Mechanical Engineering
Committee Chair/Advisor
Dr. Ge Lv
Committee Member
Dr. Yue Wang
Committee Member
Dr. Ardalan Vahidi
Committee Member
Dr. Qin Lin
Abstract
Lower-limb exoskeletons have shown great potential for assisting human locomotion, but designing controllers that provide assistance across diverse locomotor tasks and under external perturbations remains a major challenge. Many existing controllers for steady-state walking rely on pre-defined reference trajectories, which constrain voluntary human motion and limit adaptability across tasks. Moreover, they usually assume stable walking, while their performance under unstable conditions remains largely unexplored. In addition, existing gait stability augmentation controllers are often reactive rather than proactive to unstable conditions. In this dissertation, we propose control frameworks that preserve voluntary human motion while addressing two major challenges: providing task-agnostic assistance across diverse locomotor tasks and proactively augmenting gait stability under unstable postures or external perturbations.
First, we propose a control paradigm to provide task-agnostic assistance by regulating the exoskeleton torques to track the Centroidal Momentum, i.e., the sum of projected limb momenta onto the Center of Mass, of a virtual reference model generated from the user’s real-time gait, rather than from pre-defined reference kinematics. We design a nonlinear disturbance observer to estimate human joint torques and explicitly account for voluntary motion. Uniform ultimate boundedness of both the Centroidal Momentum tracking error and the observer estimation error is established theoretically. Simulations on a human-like biped show benefits from the proposed control strategy including reduced metabolic cost. Experiments with six non-disabled participants wearing a bilateral hip exoskeleton further demonstrate effectiveness across treadmill walking, stair--ground transitions, and sit-to-stand tasks, with ensemble-averaged muscle effort showing an average 22% reduction with assistance and a 21% increase with resistance.
Second, we propose a proactive control framework for gait stability augmentation under unstable postures or external perturbations while preserving voluntary human motion. The framework defines a Center-of-Mass-based stability indicator and enforces its dynamics within a user-specific safe range via control barrier functions. The control barrier function incorporates both the stability indicator and its time derivative, enabling proactive assistance when stability is rapidly deteriorating. The nonlinear disturbance observer is also incorporated in the control design to account for voluntary motion. Because it acts as a torque filter, which minimally modifies nominal torques during unstable conditions, it can be integrated with the Centroidal Momentum shaping framework to provide seamless assistance across stable and unstable gait conditions. Simulations show improved balance maintenance and recovery under perturbations. Experiments with four non-disabled participants demonstrate effectiveness in leaning tasks and steady-state walking with randomly timed slip perturbations, with average muscle-effort reductions of 41% in leaning and 21% in slipping, as well as reduced whole-body angular momentum and shorter recovery time.
Together, these control frameworks establish a broader control scheme that is both task-agnostic and stability-augmented, demonstrating the potential for agile and reliable locomotion augmentation.
Recommended Citation
Yu, Miao, "Versatile Exoskeleton Control Paradigms for Agile Human Locomotion: Task-Agnostic and Stability-Augmented Assistance" (2026). All Dissertations. 4223.
https://open.clemson.edu/all_dissertations/4223
Author ORCID Identifier
0009-0009-7818-4720
Included in
Acoustics, Dynamics, and Controls Commons, Controls and Control Theory Commons, Dynamics and Dynamical Systems Commons