Takuya Kamano

Synchronization of Two Motion Control Axes Under Adaptive Feedforward Control

In this paper, motion synchronization of two d-c motors, or motion control axes, under adaptive feedforward control is considered. The adaptive feedforward control system for each axis consists of a proportional feedback controller, an adaptive disturbance compensator and an adaptive feedforward controller. If the two adaptive systems are left uncoupled, a disturbance input applied to one of the two axes will cause a motion error in the disturbed axis only, and the error becomes the synchronization error. To achieve a better synchronization, a coupling controller, which responds to the synchronization error, i.e., the difference between the two motion errors, is introduced. In this case, when a disturbance input is applied to one axis, the motion errors appear in the undisturbed axis as well as in the disturbed axis. The motion error in the undisturbed axis is introduced by the coupling controller and the adaptive feedforward controller. The adaptive synchronization problem is formulated and analyzed in the continuous time domain first, and then in the discrete time domain. Stability conditions are obtained. Effectiveness of the adaptive synchronization controller is demonstrated by simulation.

Characteristics and Model of Ultrasonic Motor

The steady state and dynamic characteristics of an ultrasonic motor are measured. Using these results, a practical model of the ultrasonic motor is proposed. The validity of the model is verified experimentally.

Position Control System Driven by Ultrasonic Motor

The responses of position control systems driven by an ultrasonic motor are described. One system utilizes a proportional controller and the other a pulse width modulation controller. The responses of both systems for various reference positions are measured and discussed.

Design and implementation of fuzzy cooperative catching controller for multiple mobile robots

In this paper, the use of cooperative knowledge for a catching problem with multiple mobile robots is considered. To achieve successful capture of an escaping target, the robots have to move toward the escaping target after the robots drive the target into the catching area formed by themselves. Then, the cooperative knowledge is represented as the fuzzy formation rules, and used to surround the escaping target. The fuzzy formation rules are tuned by genetic algorithm in advance of experiments. The same controllers with the approach rules and the tuned fuzzy formation rules are mounted on three robots. The catching motions of three robots and the target are measured. Experimental results demonstrate that the proposed cooperation control is effective to catch the escaping target.

Autonomous mobile robot based on behavior decision skill and control skill of the operator

This paper introduces a human skill base control algorithm using artificial neural networks and fuzzy reasoning for an autonomous mobile robot. Neural networks are used to select a suitable motion control pattern in actual environments. The back propagation algorithm adjusts the weights of the neural networks so that the selected motion control pattern corresponds to the action, which is obtained by the operators behavior decision skill. To realize the selected motion control pattern, the orientation angle and the speed of the mobile robot are determined by fuzzy reasoning in which fuzzy rules are also automatically tuned so as to simulate the operators control skill. We have implemented and tested the proposed control algorithm on an autonomous mobile robot and some experimental results demonstrate the effectiveness of the proposed control algorithm for the autonomous mobile robot.

Modeling of progressive wave type ultrasonic motor

This paper describes an improved model of the progressive wave type ultrasonic motor to explain the nonlinear characteristics due to the internal friction. Some responses of motor speed to the applied voltage are calculated employing the proposed model. The calculated results are compared with the measured results.

Evolutionary Acquisition for Moving Performance of Reduced D.O.F's Quadruped Robot

In this paper, an application of genetic algorithm for evolutionary generation of initial poses of a quadruped robot reduced degrees of freedom is described. Each leg of the robot has a slider-crank mechanism to reduce the degrees of freedom and is driven by an actuator. To generate the suitable initial pose, the initial angles of four legs are coded by real number as gene and tuned by genetic algorithm under the estimation functions for forward movement and right and left rotating movement. As a result of tuning, the adequate phases shift among the legs is generated. The experimental results demonstrate that the proposed scheme is effective for generation of the suitable initial poses to achieve the successful forward and rotating movements and the robot can walk smoothly for omni-directional movement with the generated initial poses

High-Performance Positioning System with Linear DC Servo Motor under Self-tuning Fuzzy Control

This paper describes a positioning system with a linear DC servo motor (LDM) under self-tuning fuzzy control. Two types of self-tuning fuzzy controllers (STFCs), one a model reference type, the other a feedforward type, are proposed. The objectives of these two types of STFCs are to repress the influence of nonlinear characteristics of the LDM and to improve the tracking performance. The fuzzy rules in the STFC are adjusted by a tuning algorithm so that the tracking error converges to zero. The effectiveness of the proposed STFCs for improvement of the tracking performance is demonstrated by the experimental results.This paper describes a positioning system with a linear DC servo motor (LDM) under self-tuning fuzzy control. Two types of self-tuning fuzzy controllers (STFCs), one a model reference type, the other a feedforward type, are proposed. The objectives of these two types of STFCs are to repress the influence of nonlinear characteristics of the LDM and to improve the tracking performance. The fuzzy rules in the STFC are adjusted by a tuning algorithm so that the tracking error converges to zero. The effectiveness of the proposed STFCs for improvement of the tracking performance is demonstrated by the experimental results.

Output control method by adaptive control to wind power generating system

For a wind power generating system in which resistive load is connected to the DC generator for load, the development of a control method which takes out wind energy effectively even when the system characteristic is unknown is considered. The control method is a hill-climbing method, and this method can follow the quasi-maximum output relatively easily only by the measurement of output. The effectiveness of output control by the hill-climbing method was confirmed for cases of both constant and fluctuating wind velocity.<<ETX>>

DESIGN AND IMPLEMENTATION OF THE ADAPTIVE SYNCHRONIZING FEEDFORWARD CONTROLLER FOR TWO AXES MOTION CONTROL SYSTEMS

Abstract In this paper, high speed motion synchronization of two d.c. motors, or motion control axes, under adaptive feedforward control is considered. The adaptive feedforward control system for one axis system consists of a proportional feedback controller, an adaptive disturbance compensator and an adaptive feedforward controller. To synchronize the motions of the two motors, a coupling controller, which responds to the synchronization error is introduced. The synchronization error is used as the adaptation error signal in the two adaptive feedforward controllers as well. When a disturbance input is applied to one axis, the motion errors appear in the undisturbed axis as well as in the disturbed axis. The motion error in the undisturbed axis is induced by the coupling controller and adaptive feedforward controller. This allows a quick removal of the synchronization error. The effectiveness of adaptive synchronizing feedforward control is demonstrated by experiment.