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Accurately parameterizing human gait cycles is crucial for developing control systems for lower-limb wearable robots. Previous studies on characterizing human gait cycle investigated the use of human-inspired phase variables, but they lack robustness and adaptability to accommodate for transitions that occur between locomotor tasks. This paper proposes augmenting the traditional phase variables with a canonical dynamical system. This system considers the differences between the estimated and true thigh angular velocities, based on which the Fourier series coefficients and phase information will be dynamically updated via an adaptive frequency oscillator. Experiments with six able-bodied participants on level ground, inclines, and declines walking show that the augmented phase variable adapts to various locomotor tasks and transitions better than the traditional approach. 

Most current powered transfemoral prostheses are designed based on replicating normal anatomy with the inclusion of a revolute knee joint. Prosthesis users often have issues achieving proper leg length to maintain balance and perform push-off during stance, and to ensure sufficient toe clearance during swing. There is a clinical opportunity to develop a powered prosthesis that linearly shortens and lengthens during ambulation with a prismatic joint for improved leg length properties. To build on previous work, the research in this manuscript focuses on designing the physical device, the leg length actuation profile, and the control scheme. Based on gait analyses of two prosthesis users, the device provides an appropriate leg length actuation profile with sufficient shortening for toe clearance (exhibited by the greater prosthetic vs. intact side toe clearance) and lengthening for forward propulsion (exhibited by the ground reaction force peak in late stance). The device also has a motor torque and velocity capable of supporting up to a 90 kg user during normal ambulation, a control scheme with an adjustable actuation cycle based on gait cadence (matching within 2 ms), and a more compact mechanical system design (4.5 kg) less than anatomical weight requirements (5.5 kg). Additionally, the prosthesis users tested were highly encouraging of their stability, mobility, and safety while ambulating with the device. 

Task-invariant control methods for powered exoskeletons provide flexibility in assisting humans across multiple activities and environments. Energy shaping control serves this purpose by altering the human body’s dynamic characteristics in closed loop. Our previous work on potential energy shaping alters the gravitational vector to reduce the user’s perceived gravity, but this method cannot provide velocity-dependent assistance. The interconnection and damping assignment passivity-based control (IDA-PBC) method provides more freedom to shape a dynamical system’s energy through the interconnection structure of a port-controlled Hamiltonian system model. This paper derives a novel energetic control strategy based on IDA-PBC for a backdrivable knee-ankle exoskeleton. The control law provides torques that depend on various basis functions related to gravitational and gyroscopic terms. We optimize a set of constant weighting parameters for these basis functions to obtain a control law that produces able-bodied joint torques during walking on multiple ground slopes. We perform experiments with an able-bodied human subject wearing a knee-ankle exoskeleton to demonstrate reduced activation in certain lower-limb muscles. 

Task-invariant feedback control laws for powered exoskeletons are preferred to assist human users across varying locomotor activities. This goal can be achieved with energy shaping methods, where certain nonlinear partial differential equations, i.e., matching conditions, must be satisfied to find the achievable dynamics. Based on the energy shaping methods, open-loop systems can be mapped to closed-loop systems with a desired analytical expression of energy. In this paper, the desired energy consists of modified potential energy that is well-defined and unified across different contact conditions along with the energy of virtual springs and dampers that improve energy recycling during walking. The human-exoskeleton system achieves the input-output passivity and Lyapunov stability during the whole walking period with the proposed method. The corresponding controller provides assistive torques that closely match the human torques of a simulated biped model and able-bodied human subjects’ data. 

Energy shaping methods can be used to design task-invariant feedback control laws for the powered exoskeletons (i.e., orthoses). In order to achieve a desired closed-loop energy, certain matching conditions must be satisfied, which are sets of nonlinear partial differential equations. In this paper, we solve the matching conditions and come up with a new solution for under-actuated systems by using Auckly’s method.We find a unified feedback control law that is task-invariant with respect to human inputs and different contact conditions. We propose assistive and resistive shaping strategies to alter the mass/inertia matrix and simulate on a powered knee-ankle exoskeleton. The simulation results show the reduction and increment of the human model’s metabolic cost of generating muscular forces in human walking. The interchange between the kinetic and potential energy and the changes in acceleration of the center of mass are also investigated in the simulation.