Hybrid intelligent machine systems : design, modeling and control

To further improve performances of machine systems, mechatronics offers some opportunities. Traditionally, mechatronics deals with how to integrate mechanics and electronics without a systematic approach. This thesis generalizes the concept of mechatronics into a new concept called hybrid intelligent machine system. A hybrid intelligent machine system is a system where two or more elements combine to play at least one of the roles such as sensor, actuator, or control mechanism, and contribute to the system behaviour. The common feature with the hybrid intelligent machine system is thus the presence of two or more entities responsible for the system behaviour with each having its different strength complementary to the others. The hybrid intelligent machine system is further viewed from the system’s structure, behaviour, function, and principle, which has led to the distinction of (1) the hybrid actuation system, (2) the hybrid motion system (mechanism), and (3) the hybrid control system. This thesis describes a comprehensive study on three hybrid intelligent machine systems. In the case of the hybrid actuation system, the study has developed a control method for the “true” hybrid actuation configuration in which the constant velocity motor is not “mimicked” by the servomotor which is treated in literature. In the case of the hybrid motion system, the study has resulted in a novel mechanism structure based on the compliant mechanism which allows the micro- and macro-motions to be integrated within a common framework. It should be noted that the existing designs in literature all take a serial structure for micro- and macro-motions. In the case of hybrid control system, a novel family of control laws is developed, which is primarily based on the iterative learning of the previous driving torque (as a feedforward part) and various feedback control laws. This new family of control laws is rooted in the computer-torque-control (CTC) law with an off-line learned torque in replacement of an analytically formulated torque in the forward part of the CTC law. This thesis also presents the verification of these novel developments by both simulation and experiments. Simulation studies are presented for the hybrid actuation system and the hybrid motion system while experimental studies are carried out for the hybrid control system

Realization of dynamixel servo plant parameters to improve admittance control for a compliant human-robot interaction

In theory, admittance control offers a very effective method of implementing smooth human-robot interaction. It allows the user’s applied force to control the movement of a powerful robot as if the robot were a small, passive mass. However, the real-world application of admittance control faces limitation posed by the dynamics of servo motors, the accuracy of the force sensors, and the computation speed of processors. This research investigates the limitations on achieving compliant passive behavior when using state-of-the-art actuators, sensors and processors. The work involves characterizing the dynamic behavior of the servo motors, development of improved differential equations representing admittance control, and testing to determine the ability of a robotic system to represent the behavior of passivity. A method has been developed for experimentally determining the inertial, and dissipative (damping and friction) characteristics of three different models of Dynamixel motors. These parameters are optimized using data from a pendulum drop test with mass at various distances from the center of rotation. With these parameters, we assess the ability of our motor model to generate an ideal motion based upon a torque input from the user. The aim is to understand the limitations of our control paradigm to allow users to be unable to feel any difference between the performances of the passive and motor joints