Kenichi Matsuda

Self-Sensing Active Suppression of Vibration of Flexible Steel Sheet

In rolling processes, flexible steel sheet is supported by rollers and is bound to produce structural vibration. This vibration can cause severe problems to surface finish and affect the quality of the product. To overcome these problems, active vibration control has been proposed. This usually requires both sensors and actuators. The location of sensors and actuators plays a very important role in active vibration control. Moreover, a reliable sensor can be very expensive. This paper proposes a self-sensing vibration control using a push-pull type electromagnet to control the transverse vibration of the steel plate. The construction of the electromagnet has two types of coils, namely the bias coil and the control coil. Vibration displacement is estimated by using the mutual inductance change between the bias and the control coils. The estimated signal is proportional to the gap displacement. The proportional and derivative signals are fed back to the control coil to reduce the transverse vibration of the steel sheet. The proposed method is applied to a simple test rig to confirm the capability of the device. The results obtained are showing high possibility for reducing steel sheet vibration.

Proposal of Hybrid Type Active Magnetic Bearing for Turbo Machinery

New Hybrid (HB) type Active Magnetic Bearing (AMB) is proposed in this paper. It is intended to apply to high speed turbo machinery. This magnetic bearing is easily controlled by a standard linear power amplifier. The proposed magnetic bearing is analyzed and designed through Finite Element Method (FEM). The designed characteristics are compared with the standard electro-magnet type magnetic bearing. The results show good characteristics of high efficiency, good dynamic property and easy manufacturing. The proposed magnetic bearing is fabricated and the simple tests are carried out.

Hybrid Vibration Control Using Superconductor as Levitation and Velocity Sensor and Application of H.INF. Control Theory.

A new method of using a high Tc superconductor as two functions of levitation device and velocity sensor is introduced. The levitated object is controlled with an electromagnet using the measured velocity signal, that is, the system involves a hybrid magnetic levitation of superconductor pinning effect and active magnetic bearing. The experimental setup of a single degree-of-freedom system is made using a cantilever beam. A coil is wound around a permanent magnet which is used as a velocity sensor, This coil produces electromotive voltage in proportion to relative velocity. In order to insulate against vibration from the base and to reduce vibration from external force an H∞ optimum controller is designed. A simple experimental setup is made and the results obtained are discussed in detail.

Active Vibration Control of a Thin Steel Sheet

The commercial rolling process used in the steel industry to manufacture thin steel sheets tends to cause plate vibrations that lower the quality of the surface finish. This article introduces a noncontact method of active vibration control for reducing the flexural vibrations of a thin steel sheet. The proposed electromagnetic method of control has been implemented in a simple experimental setup where the signal from a motion sensor regulates the attractive force of the magnets that produce a damping force on the steel sheet.

High-speed control and adaptive control of a robot arm.

A 16-bit parallel data controlled robot is made which can easily be controlled by a personal computer. Fist, the trajectory is planned to calculate the driving torque which compensates for the dynamic reflection of the robot. The trajectory and the driving torque are fed through the parallel port to produce the fast motion of the robot. However, the dynamic property of the robot will change according to the arm position. The computer monitors both actuating signals and controlled position. After one cycle of robot motion. the auto regressive method is applied to identify the robot dynamics. These data are used to calculate a more accurate driving force which is fed to the robot controller on the next motion. The results obtained clarify the ability to identify inertia and damping factors.