A serial robotic manipulator arm is a complex electro-mechanical system whose performance is primarily characterized by the internal parameters of its actuators. The actuator itself is a complex nonlinear system whose performance can be characterized by the speed and torque capabilities of its motor and its accuracy depends on the resolution of the encoder as well as its ability to resist deformations in its gear train under load. The mechanical gain associated with the gear train transmission is critical to the overall performance of the actuator since it amplifies the motor torque thus improving the force capability of the manipulator housing it, reduces the motor speed to a suitable output speed operating range, dominates the inertia content of the manipulator and amplifies the stiffness improving the precision under load of the overall system. In this work, a basic analytic process that can be used to manage the actuator parameters to obtain an improved arm design based on a set of desired/required performance specifications is laid out. The key to this analytic process is the mapping of the actuator parameters (motor speed, motor torque, rotary stiffness, encoder resolution, transmission efficiency, mass, rotary inertia) to their effective values at the system output via the mechanical gains of the actuator transmissions as well as the effective mechanical gains associated with the manipulator geometry. This forward mapping of the actuator parameters allows the designer to determine how each of the actuator parameters influences the functional capacity of the serial manipulator arm. The analytic formulation is demonstrated to be effective in addressing the issue of configuration management of serial robotic manipulators where the goal is to assemble a system from a finite set of actuator modules that meets some required performance specifications. To this end, four design case studies demonstrating the solution of the configuration management problem are presented where the application domains include designing for light to heavy-duty force applications, designing for responsiveness and designing for Human-Robot Interactions (HRI). The design trade-offs for each of the application domains are analyzed and design guidelines are presented. This research also formulates a new approach to characterizing the dynamic behavior of serial chain mechanisms via the kinetic energy distribution. In any mechanism, the amount of kinetic energy in the system is a very important quantity to analyze. Since the inertial torques are directly related to the rate of change of the kinetic energy, better design (and operation) is achieved by having an understanding of how kinetic energy is distributed along the mechanism structure as well as how rapidly kinetic energy is flowing within it. In this work, a description of the Kinetic Energy Partition Values (KEPV) for serial chain mechanisms, as well as their rates of change, are presented. The KEPVs arise from the partitioning of the mechanism’s kinetic energy. Two design criteria, one based on the KEPVs and another based on their rates of change, are developed. These design criteria are indicators of both the dynamic isotropy of the system as well as the amount of kinetic energy flow within the system. A six-axis spatial manipulator is used to illustrate the solution of a design optimization problem where the goal is to demonstrate how the inertial parameters of the actuators and mechanical gains of the actuator transmissions alter the kinetic energy of the system which is “measured” via an effective mass criterion and its distribution which is measured via the KEPV criterion. It is demonstrated that the mechanical gains in the actuators significantly influence the magnitude of the kinetic energy as well as its distribution within the system. / text

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

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The control law that is investigated in this thesis is referred to as the acceleration feedback control law, first introduced by (Luo and Saridis 1983). The study of the error performance of this control law under non-ideal conditions is the subject of this thesis. A design methodology evolves from the theoretical foundations of the acceleration feedback control law. The design methodology yields a robust, high performance closed loop robot manipulator system. Design experiments are performed on a PUMA 600 robot manipulator and the closed loop performance is analyzed by simulation study. / The control law objective is to ensure that the manipulator joint coordinate trajectory is maintained with respect to a desired joint trajectory. The stability and error performance properties of the acceleration feedback control law are analytically examined by a Lyapunov stability analysis. The effects of integral control and computed torque augmentation are also examined in the stability and error performance analysis. The robustness properties, in the presence of high frequency unstructured uncertainties, are examined by classical frequency domain techniques. The theoretical results are verified by simulation. The simulation model test-bed is based on a PUMA 600 robot manipulator which is used throughout the thesis to support theoretical results. / The goal of this thesis is in presenting the acceleration feedback control law with an accompanying design methodology as a practical robot manipulator control law. The design methodology allows robot manipulator system designers to implement this control law as a simple, inexpensive, microprocessor based servomechanism at each joint. The theoretical development not only accounts for the intrinsic design trade-offs but also assures designers that the implementation will yield a robust, high performance closed loop system. This detailed design methodology is presented and a sample design is carried out and verified by simulation. The effects due to sampling, quantization, friction and frequency uncertainty are included in the simulation study.

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