• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.2
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• pp.145-154
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• 2023

In this study, to control the heading angle of a ship, which is constantly subjected to various internal and external disturbances during the voyage, an LADRC (linear active disturbance rejection control) design that focuses more on improving the disturbance removal performance was proposed. The speed rate of change of the ship's heading angle due to the turn of the rudder angle was selected as a significant factor, and the nonlinear model of the ship's maneuvering equation, including the steering gear, was treated as a total disturbance. It is the similar process with an LADRC design for the first-order transfer function model. At this time, the gains of the controller included in LADRC and the gains of the extended state observer were tuned to RCGAs (real-coded genetic algorithms) to minimize the integral time-weighted absolute error as an evaluation function. The simulation was performed by applying the proposed GA-LADRC controller to the heading angle control of the Mariner class vessel. In particular, it was confirmed that the proposed controller satisfactorily maintains and follows the set course even when the disturbances such as nonlinearity, modelling error, uncertainty and noise of the measurement sensor are considered.

• Aerospace Engineering and Technology
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• v.3 no.2
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• pp.160-169
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• 2004

In order to get the high resolution satellite image, MSC has TDI function in the KOMPSAT-2. So it is required to control the yaw angle of the attitude as operation concepts of KOMPSAT-2. This study was to explain the TDI function, to set up the geometric equation to satisfy the condition, and finally to determine the equation of yaw angle. The calculating program was developed and simulated with orbit and imaging attitude as input data, and the results were compared with the yaw steering values calculated in the on-board computer.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.699-703
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• 2004

The autopilot system targets decreasing labor, working environment, service safety security and elevation of service efficiency. Ultimate purpose is minimizing number of crew for guarantee economical efficiency of shipping service. Recently, being achieving research about Course Keeping Control, Track Keeping Control, Roll-Rudder Stabilization, Dynamic ship Positioning and Automatic Mooring Control etc. which compensate nonlinear characteristic using optimizing control technique. And application research is progressing using real ship on actual field. Relation of Rudder angle which adjusted by Steering Machine and ship-heading angle are non-linear. And, Load Condition of ship acts as non-linear element that influence to Parameter of ship. Also, because the speed of a current and direction of waves, velocity and quantity of wind etc. that id disturbance act in non-linear form, become factor who make service of shipping painfully. Therefore, service system of shipping requires robust control algorithm that can overcome nonlinearity. In this paper, Using GA algorithm,design autopilot system of ship that could overcome the non-linear factor of ship and disturbance and examined result through simulation.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.5
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• pp.257-263
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• 2022

Active stabilizers use signals such as steering angle, yaw rate, and lateral acceleration to vary the roll stiffness of the front and rear suspension depending on the vehicle's driving conditions, and are attracting attention as RSC (Roll Stability Control) system that suppresses roll when turning and improves ride comfort when going straight. Various studies have been conducted in relation to active stabilizer bars and RSC systems. However, accurate modeling of passive stabilizer model and active stabilizer model and vehicle dynamics analysis result verification are insufficient, and performance result analysis related to vehicle roll angle estimation and electric motor control is insufficient. Therefore, in this study, an accurate vehicle dynamics model was constructed by measuring the passive/active stabilizer bar model and component parameters. Based on this, the analysis result with high reliability was derived by comparing the roll angle estimation algorithm based on the lateral acceleration and suspension of the vehicle with the actual vehicle driving test result. In addition, it was intended to accurately analyze the motor torque characteristics and roll reduction effects of the electric motor-driven RSC system.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.3
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• pp.338-343
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• 1999

In this paper, the fuzzy neural network for the obstacle avoidance, which consists of the straight-line navigation and the barrier elusion navigation, is proposed and examined. For the straight-line navigation, the fuzzy neural network gets two inputs, angle and distance between the line and the mobile robot, and produces one output, steering velocity of the mobile robot. For the barrier elusion navigation, four ultrasonic sensors measure the distance between the barrier and the mobile robot and provide the distance information to the network. Then the network outputs the steering velocity to navigate along the obstacle boundary. Training of the proposed fuzzy neural network is executed in a given environment in real-time. The weights adjusting uses the back-propagation of the gradient of error to be minimized. Computer simulations are carried out to examine the efficiency of the real time learning and the guiding ability of the proposed fuzzy neural network. It has been shown that the mobile robot that employs the proposed fuzzy neural network navigates more safely with and less trembling locus compared with the previous reported efforts.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.166-171
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• 1989

In the view of the fact that mobile robot in nuclear facilities should be able to turn in narrow space, go over obstacles, and climb stairs for the inspection and maintenance, a robot, named as KAEROT, is developed. It adopts 2DWIS (2-Driving Wheels, 1-Steering) and has three planetary wheels that are composed of two star-like arms and three small wheels. The experiments were carried out in two locomotion methods; (1) by controlling the rear wheel speed as a function of steering angle, and (2) by using inclination and stair-detection sensor to control the position of planetary and small wheel. The developed robot moved on the floor with stability. Results from the experiment on the rectangular obstacle as well as the computer simulation showed a feasibility on the stairs.

• Journal of Auto-vehicle Safety Association
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• v.7 no.2
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• pp.32-38
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• 2015

A sine with dwell test is well known as a test scenario for evaluation of performance of electronic stability control(ESC) on passenger vehicles and heavy commercial vehicles. However, when it comes to ESC for medium commercial vehicles, the test scenario has not been established yet. In this paper, the sine with dwell test was modified considering characteristics of medium commercial vehicles. The three main modifications of the original test scenario are the steering angle level, steering frequency, and loading condition of the vehicle. These modifications are derived from simulation study for different medium commercial vehicles. From simulation study, it was shown that the ESC system for medium commercial vehicle is objectively evaluated by the proposed test scenario. A clear improvement on vehicle stability was seen in the results when ESC system was used.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.6
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• pp.269-279
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• 2020

This paper presents the design and implementation of embedded systems and autonomous path generation for autonomous speed sprayer. Autonomous Orchard Systems can be divided into embedded controller and path generation module. Embedded controller receives analog sensor data, on/off switch data and control linear actuator, break, clutch and steering module. In path generation part, we get 3D cloud point using Velodyne VLP16 LIDAR sensor and process the point cloud to generate maps, do localization, generate driving path. Then, it finally generates velocity and rotation angle in real time, and sends the data to embedded controller. Embedded controller controls steering wheel based on the received data. The developed autonomous speed sprayer is verified in test-bed with apple tree-shaped artworks.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.7 no.2
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• pp.147-156
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• 1996

In this paper we proposed a beam steering equation for the planar slotted waveguide array antenna. The tilt angle measured from the rotating axis and the aperture distribution of the antenna were the most important factors for the beam steering. From the equation, we calculated the frequency and phase distribution of the aperture for any desired beam direction. And we developed a high speed control algorithm delivering the phase data to the phase shifters of a one-dimensional phased array antenna. To reduce complexity of the control circuit and the phase delivery time, we proposed the serial phase repeating method. Because of its simplicity, we expect it can be useful for a large 2- dimensional fully phased array antenna.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.550-557
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• 1999

This paper describes a road-following controller using the proposed neural network for autonomous vehicle. Road-following with visual sensor like camera requires intelligent control algorithm because analysis of relation from road image to steering control is complex. The proposed neural network, relative similarity modular network(RSMN), is composed of some learning networks and a partitioniing network. The partitioning network divides input space into multiple sections by similarity of input data. Because divided section has simlar input patterns, RSMN can learn nonlinear relation such as road-following with visual control easily. Visual control uses two criteria on road image from camera; one is position of vanishing point of road, the other is slope of vanishing line of road. The controller using neural network has input of two criteria and output of steering angle. To confirm performance of the proposed neural network controller, a software is developed to simulate vehicle dynamics, camera image generation, visual control, and road-following. Also, prototype autonomous electric vehicle is developed, and usefulness of the controller is verified by physical driving test.