Arata Ejiri

Micro-G emulation system using constant-tension suspension for a space manipulator

A hardware system for emulating microgravity for an on-the-ground space manipulator is described. The manipulator is suspended by wires, kept vertical by the suspension arms controlled to follow the manipulators motion. The manipulator base is supported by a six-degree-of-freedom mechanism, with which free floating is emulated based on the numerical integration of the dynamic and kinematic equations for the manipulator. The gravitational force acting on the manipulator is thus canceled by the combination of the contact force on the base and the upward tensile forces through the wires. Optimizing the manipulators suspension keeps the values of individual tensions acting on it constant, whatever the manipulators attitude. Experiments show that the suspension system is sensitive enough to emulate the vertical free-floating motion of a suspended object, and can be tuned to initiate a microgravity environment of at least 0.01 g under restricted conditions.<<ETX>>

Satellite berthing experiment with a two-armed space robot

To study autonomous control of a space robot, the authors developed their Advanced Space Robot Testbed with Redundant Arms (ASTRA). Berthing a satellite moving in space is a difficult and dangerous task when done manually. This paper describes a robot which berthed a mockup satellite moving and rotating in zero gravity. Features of the robot include autonomous approach to a moving target satellite using visual satellite motion estimation, using real-time visual tracking control to track satellite handles with two robot arms, and grasping the satellite handles with minimum mechanical shock using a flexible wrist mechanism and impedance control. The authors ran their satellite berthing experiment on the ASTRA to check its performance.<<ETX>>

A Fast Model Predictive Control Algorithm for Diesel Engines

Abstract For protecting the environment, several studies have been conducted for improving clean-burning diesel engines. One such study focused on applying model predictive control (MPC) to a diesel engine intake system. The main issue of this policy is computational time. Therefore, we propose a fast MPC algorithm for diesel engines. Our approach consists of linearization of a nonlinear air intake system model, relaxation of control input constraints by using penalty functions, and algebraic reduction of the number of variables of a system of equations, which we have to solve for obtaining control inputs.