• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 추계학술대회 논문집
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• pp.236-243
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• 2007

Steering systems are classified as FWS(front-wheel steering), RWS(rear-wheel steering) and AWS(all-wheel steering) according to steering position. AWS is effective to reduce turning radius and platform length because all wheels are steered. Although various rear wheel control logics for AWS were developed, these are applied to four wheel steering cars. Therefore new control logics must be developed to apply articulated vehicles. In the present study, it is suggested how to control the real wheels based on the virtual rigid axles and also how to set it to minimize the turning radius.

• 한국정밀공학회지
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• 제17권5호
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• pp.173-179
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• 2000

While a cutting tool is machining a workpiece at various cutting depth, the feedrate is usually selected based on the maximum depth of cut. Even if this selection can avoid power saturation or tool breakage, it is very conservative compared to the capacity of the machine tools and can reduce the productivity significantly. Many adaptive control techniques that can adjust the feedrate to maintain the constant cutting force have been reported. However, these controllers are not very widely used in manufacturing industry because of the limitations in measuring the cutting force signals. In this paper, turning force control systems based on the estimated cutting force signals are proposed. A synthesized cutting force monitor is introduced to estimate the cutting force as accurately as a dynamometer does. Three control strategies of PI, adaptive and fuzzy logic controllers are applied to investigate the feasibility of utilizing the estimated cutting force fur turning force control. The experimental results demonstrate that the proposed systems can be easily realized in CNC lathe with requiring little additional hardware.

• 한국항해항만학회지
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• 제30권2호
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• pp.119-124
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• 2006

In Part I(theoretical study) of the paper, a new adaptive autopilot for ships based on Adaptive Neural Networks was proposed. The ANNAI autopilot was designed for course-keeping, turning and track-keeping control for ships. In this part of the paper, to show the effectiveness and feasibility of the ANNAI autopilot and automatic selection algorithm for learning rate and number of iterations, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances are presented. Additionally, the results of the previous studies using Adaptive Neural Network by backpropagation algorithm are also showed for comparison.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2005년도 추계학술대회 논문집
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• pp.17-22
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• 2005

This paper presents a new adaptive autopilot for ships based on the Adaptive Neural Networks. The proposed adaptive autopilot is designed with some modifications and improvements from the previous studies on Adaptive Neural Networks by Adaptive Interaction (ANNAI) theory to perform course-keeping, turning and track-keeping control. A strategy for automatic selection c! the neural network controller parameters is introduced to improve the adaptation ability and the robustness of new ANNAI autopilot. In Part II of the paper, to show the effectiveness and feasibility of the proposed ANNAI autopilot, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances are presented.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2005년도 추계학술대회 논문집
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• pp.23-28
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• 2005

In Part I (theoretical study) of the paper, a new adaptive autopilot for ships based on Adaptive Neural Networks was proposed. The ANNAI autopilot was designed for course-keeping, turning and track-keeping control for ships. In this part of the paper, to show the effectiveness and feasibility of the ANNAI autopilot, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances are presented. Additionally, the results of the previous studies using Adaptive Neural Network by backpropagation algorithm are also showed for comparison.

• 한국항해항만학회지
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• 제29권9호
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• pp.771-776
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• 2005

This paper presents a new adaptive autopilot for ships based on the Adaptive Neural Networks. The proposed adaptive autopilot is designed with some modifications and improvements from the previous studies on Adaptive Neural Networks by Adaptive Interaction (ANNAI) theory to perform course-keeping, turning and track-keeping control. A strategy for automatic selection of the neural network controller parameters is introduced to improve the adaptation ability and the robustness of new ANNAI autopilot. In Part II of the paper, to show the effectiveness and feasibility of the proposed ANNAI autopilot, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances will be presented.

• 한국정밀공학회지
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• 제20권3호
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• pp.74-81
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• 2003

This paper introduces that the turning center optimizes main and sub spindle's synchronized controller in Open-CNC. In view of optimal design, the mathematical modeling and the frequency domain analysis of spindle's system are simulated. For the minimizing of synchronized error in each spindle's speed, the study of control method and the related control parameter is proposed. By the experiment in prototype machines using the server/client program, the validity of the proposed synchronous error's compensation method is verified.

• Journal of Biosystems Engineering
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• 제38권4호
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• pp.255-263
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• 2013

Purpose: It is not easy to drive a rice-transplanter avoiding underlapped or overlapped transplanting in paddy fields. An automated guidance system for the riding-type rice-transplanter would be necessary to operate the rice-transplanter autonomously or to assist the beginning drivers as a driving aid. Methods: A prototype of guidance system was composed of embedded computers, RTK-GPS, and a power-steering mechanism. Two Kalman filters were adopted to overcome sparse positioning data (1 Hz) from the RTK-GPS. A global Kalman filter estimated the posture of rice-transplanter every one second, and a local Kalman filter calculated the posture from every new estimation of the global Kalman filter with an interval of 200 ms. A PID controller was applied to the row-following mode control. A control method of U-turning mode was developed as well. A stepping motor with a reduction gear set was used to rotate the shaft of steering wheel. Results: Test trials for U-turning and row-following modes were done in a paddy field after some parameters have been tuned at the ground speed range of 0.3 ~ 1.2 m/s. The minimum RMS error of offset was 3.13 cm at the ground speed of 0.3 m/s while the maximum RMS error was 13.01 cm at 1.2 m/s. The offset RMS error tended to increase as the ground speed increased. The target point distance, LT also affected the system performance and PID controller parameters should be adjusted on different ground speeds. Conclusions: A target angle-based PID controller plus stationary steering angle controller made it possible for the rice-transplanter to steer autonomously by following a reference line accurately and even on U-turning mode. However, as condition in paddy fields is very complicated, the system should control the ground speed that prevents it from deviating too much due to ditch and slope.

• 제어로봇시스템학회논문지
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• 제20권2호
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• pp.223-231
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• 2014

Humanoid robot is the most suitable robot platform for effective human interaction and various intelligent services. The present work addresses development of real time wireless control application of humanoid robot's forward and backward walks, and turning in walking. For convenience of human users, the application is developed on Android OS (Operating System) working on his or her smartphone. To this end, theoretic background on various-directional biped walking is proposed based on joint trajectories for forward walking, which have been shaped with a global optimization method. In this paper, backward walking is scheduled by interchange of angles and angular velocities and additional change of signs in angular velocities at all the via-points connecting cubic polynomial trajectories. Turning direction in walking is also implemented by activating the transversal hip joint initially located in the support leg in two stages. After validation of the proposed walking schemes with Matlab simulator, a smartphone application for the omnidirectional walking has been developed to control a humanoid robot platform named DARwIn-OP interconnected via Wi-Fi. Experiment result of the present wireless control of a humanoid robot with smartphone is successful, and the application will be released in application market near future.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.