This study introduces quasi-real-time (QRT) motion control, explicitly incorporating measured sampling periods into the digital control loop. Digital control in mechatronic systems typically relies on the assumption of fixed sampling periods. However, practical systems often experience sampling fluctuations due to hardware limitations, sensor-related interrupt processing, and communication delays. To address this issue, a systematic discretization method for continuous-time transfer functions is proposed to enable controller, observer, and filter design under sampling fluctuations. Experimental results demonstrate that the proposed approach performs more robustly than conventional fixed-sampling implementations. QRT motion control relaxes stringent real-time (RT) constraints and is a foundation for user-friendly, general-purpose operating system (GPOS)-based RT execution frameworks in advanced mechatronic applications.

In this paper, the structure of a model to estimate human motion from surface-electromyography (sEMG) was defined mathematically and physically. Especially, an infinite impulse response (IIR) filter and an element description method were focused to generate the model in this paper. Human motion can be estimated from sEMG. However, the relationship between sEMG and human motion has a complex characteristics such as a non-linear relationship. The cause of the above complex relationship can be thought the muscle contraction velocity. Then, the IIR filter was applied to consider about the previous sEMG value in the estimation. In addition, some conventional models have been a black-box model and it is not easy to interpret the model mathematically and physically. From the above, an element description method (EDM) was applied to generate the model in this paper. EDM is one of the system identification method and it is easy to interpret the model mathematically and physically because EDM can generate the block diagram of the model.In this way, the proposed method could solve two conventional methods about the muscle contraction velocity and the black box model. Then, it was possible to define the structure of the model by the above in this paper. In this paper, the models about a wrist and a fingertip motion were generated and considered about the structure. As the results, the structure of models was defined with a hyperbolic tangent function. It will be possible to apply the model to various motions by just identifying the parameters about the relationship between each joint and muscle because the amount of muscles and range of sEMG are deferent from each muscle.

Vibration suppression has attracted interest in achieving fast, stable motion control in industrial fields. This study uses the wave partial differential equation (PDE) to model resonant systems and connects a lumped load and the PDE model in series. The lumped load is governed by the ordinary differential equation (ODE). This integrated model replaces the conventional two-mass resonant model, referred to as the PDE-ODE model in this study. A matrix representation of the PDE model is eigenvalue decomposed. The decomposition provides the basis transformation of the variables on the actual space into those on a wave space. Based on this transformation, the proposed controller equips the decoupling of the traveling/reflected waves for vibration suppression. Impedance matching explains the conditions necessary for the decoupling and control of vibration. The suppression method requires only the PDE part's parameter, making the control system resistant to inertial variations.

Recently, the rational motion of robots is required for further applications. Human motion gives many clues to studies of robotics. This study focuses on the fact that a human adjusts grip force when he/she performs an impact motion with a tool. The tools often have elasticity, and the human adjustment enables an effective impact motion. For reproduction of the impact motion with a flexible manipulator, this study models the elasticity as a wave system. The flow of the reflected wave is controlled during the impact motion based on the human adjustment of grip force. Since this study is based on the research of vibration suppression in elastic structures, it provides not only rational but also stable motion control. The experimental results show the validity of the proposed method.