Biologically-inspired Motion Control for Kinematic Redundancy Resolution and Self-sensing Exploitation for Energy Conservation in Electromagnetic Devices

This thesis investigates particular topics in advanced motion control of two distinct mechanical systems: human-like motion control of redundant robot manipulators and advanced sensing and control for energy-efficient operation of electromagnetic devices. Control of robot manipulators for human-like motions has been one of challenging topics in robot control for over half a century. The first part of this thesis considers methods that exploits robot manipulators’ degrees of freedom for such purposes. Jacobian transpose control law is investigated as one of the well-known controllers and sufficient conditions for its universal convergence are derived by using concepts of “stability on a manifold” and “transferability to a sub-manifold”. Firstly, a modification on this method is proposed to enhance the rectilinear trajectory of the robot end-effector. Secondly, an abridged Jacobian controller is proposed that exploits passive control of joints to reduce the attended degrees of freedom of the system. Finally, the application of minimally-attended controller for human-like motion is introduced. Electromagnetic (EM) access control systems are one of growing electronic systems which are used in applications where conventional mechanical locks may not guarantee the expected safety of the peripheral doors of buildings. In the second part of this thesis, an intelligent EM unit is introduced which recruits the selfsensing capability of the original EM block for detection purposes. The proposed EM device optimizes its energy consumption through a control strategy which regulates the supply to the system upon detection of any eminent disturbance. Therefore, it draws a very small current when the full power is not needed. The performance of the proposed control strategy was evaluated based on a standard safety requirement for EM locking mechanisms. For a particular EM model, the proposed method is verified to realize a 75% reduction in the power consumption

DEVELOPMENT OF A PROTOTYPE SMART APPAREL TO QUANTIFY RUNNING GAIT IN THE DAILY TRAINING ENVIRONMENT

Running gait kinetics and kinematics can be measured in the lab using force-instrumented treadmills and 3D motion capture. However, these tools are not feasible for use in the daily training environment of recreational and elite runners and track athletes. An inertial sensor-based prototype wearable smart garment (SG) has been developed to solve this problem. The purpose of this study was an initial assessment of SG compared to a force treadmill (FT) where foot-ground kinetics and temporal measures relevant to running were examined. Vertical ground reaction force, step time, and contact time showed “good to excellent” mean absolute percent error (\u3c 6%), while step impulse did not (\u3e 10%). All variables showed strong correlations between SG and FT (r \u3e 0.85). The initial prototype smart garment is a viable option for the measurement of running biomechanics outside of the lab

TOWARDS A “MORE VALID” METHOD OF VALIDATION: APPLICATION OF EFFECTIVE MASS FOR ERROR RESOLUTION OF FORCE PLATE MEASUREMENTS

We introduce effective mass as the preferred alternative to total system mass when analyzing a multi-link model of the human body. Effective mass is defined as the mass that would have equivalent motion characteristics at the point of force application if substituted for the whole system. We demonstrate our findings by deriving formulations for loaded back squat and bench press exercises. Our results suggest that force-plate-derived metrics such as velocity and power contain non-trivial errors when total system mass is used to infer kinematics of external loads. We elaborate on the sources of these errors and how they can compromise the assessment of the validity or reliability of other devices, such as linear position transducers and IMU-based tools