This thesis presents a hierarchical geometric control approach for fast and energetically fiecient bipedal dynamic walking in three-dimensional (3-D) space to enable motion planning applications that have previously been limited to ineficient quasi-static walkers. In order to produce exponentially stable hybrid limit cycles, we exploit system energetics, symmetry, and passivity through the energy-shaping method of controlled geometric reduction. This decouples a subsystem corresponding to a lower-dimensional robot through a passivity-based feedback transformation of the system Lagrangian into a special form of controlled Lagrangian with broken symmetry, which corresponds to an equivalent closed-loop Hamiltonian system with upper-triangular form. The first control term reduces to mechanically-realizable passive feedback that establishes a functional momentum conservation law that controls the «divided» cyclic variables to set-points or periodic orbits. We then prove extensive symmetries in the class of open kinematic chains to present the multistage application of controlled reduction. A reduction-based control law is derived to construct straightahead and turning gaits for a 4-DOF and 5-DOF hipped biped in 3-D space, based on the existence of stable hybrid limit cycles in the sagittal plane-of-motion. Given such a set of asymptotically stable gait primitives, a dynamic walker can be controlled as a discrete-time switched system that sequentially composes gait primitives from step to step. We derive «funneling» rules by which a walking path that is a sequence of these gaits may be stably followed by the robot. The primitive set generates a tree exploring the action space for feasible walking paths, where each primitive corresponds to walking along a nominal arc of constant curvature. Therefore, dynamically stable motion planning for dynamic walkers reduces to a discrete search problem, which we demonstrate for 3-D compass-gait bipeds. After reecting on several connections to human biomechanics, we propose extensions of this energy-shaping control paradigm to robot-assisted locomotor rehabilitation. This work aims to oer a systematic design methodology for assistive control strategies that are amenable to sequential composition for novel progressive training therapies.

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In this research, a power-assist, lower-limb orthosis is developed to help the elderly or people suffering sports injuries walk or climb stairs. In the pneumatic muscle used for actuation, it is found that hysteresis phenomenon exists during the inflation–deflation process and such a phenomenon deteriorates the control performance. In order to eliminate the influence of hysteresis on the control system, a hysteresis model is constructed and used to devise an inverse control for feedforward compensation. The inverse control is combined with loop transfer recovery (LTR) feedback control to achieve better tracking performance. Moreover, bumpless switching compensators are also incorporated into the combined control system to ensure smooth switching between different phases of operation. To verify that the developed orthosis can effectively accomplish the assistive function, a human subject wearing the orthosis is asked to walk and to climb stairs. Experiments indicate that the orthosis is indeed helpful in assisting human locomotion.

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This contribution presents a new approach of estimating the joint torques for an active orthosis. The new approach combines inverse dynamics and measured ground reaction forces. The joint torques can easily be computed from the ground reaction forces, but the measurement is usually awed. An obsererver is employed to estimate the disturbance of the measurements and restore the original joint torques. A model of the human lower extremity is presented and additional seat forces are introduced to model the seat. Simulation results on the Sit-to-Stand movement illustrate the eectivity of the new approach.

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The paper suggests a conceptual model for systems design in biomecha-tronics based on the ideas of mathematics&cybernetics originated by systems theory. Traditional mathema-tical models and models of artificial intelligence do not allow describing biomechatronic systems being designed on all its levels in one common formal basis, i.e. they do not give connected descriptions of the systems structure, the system as dynamic unit in its environment and the environment construction. So, the models of hierarchical and dynamic systems were chosen as a theoretical means for design&control tasks solving in biomechatronics. Theoretical construction of the conceptual model proposed in form of aed (standard block of hierarchical systems) is considered. The example of the model application in the description of Human-Exoskeleton system taking into account its biomechatronic subsystems is presented after that.

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The level of motivation or stress influences learning the use of a robot-assist device for walking. Heart rate asymmetry (HRA) indicates the level of parasympathetic (HRA<0.5) and sympathetic (HRA>0.5) involvement in heart rate regulation. Three patients and seven controls were presented increasing levels of task difficulty. During training patients showed an increase in stress as indicated by the HRA index (0.524±0.02) in contrast to control participants (0.485±0.03). As the task complexity increased, the HRA in the patient group was atypical and falling below 0.5, compared to control (HRA>0.5). The latter result reflects an increas-ed cognitive involvement and a higher sympathetic predominance in accordance with an increased task difficulty. Thus stroke affected the response to the task challenges in that the patient response to increasing task challenge leads to an inversion of HRA associated with a decreased mental engagement and higher risk of sudden cardiac death.

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