• 한국산학기술학회논문지
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• 제17권11호
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• pp.1-9
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• 2016

열차제어시스템은 지상 전기 중심에서 차상 통신 중심으로 변화하고 있다. 최신의 열차제어시스템인 CBTC 시스템은 차상과 지상시스템 간 양방향 무선통신을 기반으로 높은 간격제어 효율을 가진다. 하지만 지상이 제어의 중심이 되고 있기 때문에 하나의 지상시스템이 허용할 수 있는 열차 투입 대수가 제한되고 차상과 지상제어시스템 간 cyclic-path 제어흐름으로 인해 운전시격 단축에 한계를 가진다. 본 논문은 열차자율주행제어시스템을 위한 간격제어와 차상중심 분산형 연동 알고리즘을 제안한다. 열차자율주행제어시스템은 차상에서 간격제어와 함께 분기제어를 수행하므로 선로와 분기기는 공유자원인 동시에 세마포어 요소이다. 제안된 열차자율주행기반 간격제어는 지상 제어시스템의 제어명령에 의존하지 않고 열차와 열차 또는 선로변 설비와의 직접적인 무선통신을 통해 열차 간격제어를 수행한다. 제안된 연동 알고리즘은 공유자원인 선로전환기가 동시에 두 대 이상의 열차가 점유하지 못하도록 선로전환기 고유 key를 이용한 세마포어 기법을 새롭게 정의한다. 시뮬레이션을 통해 제안된 열차자율주행제어시스템의 향상된 간격제어 성능을 확인하며, 차상중심 분산형 연동알고리즘과 기존의 연동장치에서 수행하던 여러 연동논리를 비교함으로써 단순화된 연동알고리즘으로 안전한 열차제어가 가능함을 확인한다.

• International Journal of Control, Automation, and Systems
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• 제2권3호
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• pp.374-383
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• 2004

This paper presents a neural network adaptive controller for autonomous diving control of an autonomous underwater vehicle (AUV) using adaptive backstepping method. In general, the dynamics of underwater robotics vehicles (URVs) are highly nonlinear and the hydrodynamic coefficients of vehicles are difficult to be accurately determined a priori because of variations of these coefficients with different operating conditions. In this paper, the smooth unknown dynamics of a vehicle is approximated by a neural network, and the remaining unstructured uncertainties, such as disturbances and unmodeled dynamics, are assumed to be unbounded, although they still satisfy certain growth conditions characterized by 'bounding functions' composed of known functions multiplied by unknown constants. Under certain relaxed assumptions pertaining to the control gain functions, the proposed control scheme can guarantee that all the signals in the closed-loop system satisfy to be uniformly ultimately bounded (UUB). Simulation studies are included to illustrate the effectiveness of the proposed control scheme, and some practical features of the control laws are also discussed.

• 한국인공지능학회지
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• 제12권3호
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• pp.9-15
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• 2024

This paper addresses the critical need for quadcopters in GPS-denied indoor environments by proposing a novel attitude control mechanism that enables autonomous navigation without external guidance. Utilizing AR marker detection integrated with a dual PID controller algorithm, this system ensures accurate maneuvering and positioning of the quadcopter by compensating for the absence of GPS, a common limitation in indoor settings. This capability is paramount in environments where traditional navigation aids are ineffective, necessitating the use of quadcopters equipped with advanced sensors and control systems. The actual position and location of the quadcopter is achieved by AR marker detection technique with the image processing system. Moreover, in order to enhance the reliability of the attitude PID control, the dual closed loop control feedback PID control with dual update periods is suggested. With AR marker detection technique and autonomous attitude control, the proposed quadcopter system decreases the need of additional sensor and manual manipulation. The experimental results are demonstrated that the quadrotor's autonomous attitude control and operation with the dual closed loop control feedback PID controller with hierarchical (inner-loop and outer-loop) command update period is successfully performed under the non-GPS aided indoor environment and it enhanced the reliability of the attitude and the position PID controllers within 17 seconds. Therefore, it is concluded that the proposed attitude control mechanism is very suitable to GPS-denied indoor environments, which enables a quadcopter to autonomously navigate and hover without external guidance or control.

• 융합신호처리학회논문지
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• 제4권4호
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• pp.58-65
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• 2003

기존의 횡 방향제어 알고리즘은 도로에서 발생할 수 있는 변수를 고려하여 알고리즘을 작성해야 했다. 이러한 제어 알고리즘을 작성하기 위해서는 주행해야 하는 도로에 따라 파라미터를 재조정해야 하는 문제와 대량의 계산이 요구되는 모델링 문제가 있었다. 본 논문에서는 지능적 횡 방향제어가 가능한 학습알고리즘에 관해 연구하였다. 학습알고리즘은 인공지능 알고리즘 중 자기구성 알고리즘을 사용하였으며 학습데이터는 도로의 특징점을 이용하였다. 컴퓨터를 이용한 시뮬레이션 결과 본 논문의 학습알고리즘에 의한 조향제어가 가능한 것을 알 수 있었고 실제로 주행이 가능한 자율이동로봇에 적용하여 학습에 의한 횡 방향제어가 가능한 것을 확인하였다.

• 대한조선학회논문집
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• 제58권2호
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• pp.121-128
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• 2021

According to the increasing interest and demand for the Autonomous Surface Vessels (ASV), the autonomous navigation system is being developed such as obstacle detection, avoidance, and path planning. In general, autonomous navigation algorithm controls the ship by detecting the obstacles with various sensors and planning path for collision avoidance. This study aims to construct and prove autonomous algorithm with integrated various sensor using the Robot Operating System (ROS). In this study, the safety zone technique was used to avoid obstacles. The safety zone was selected by an algorithm to determine an obstacle-free area using 2D LiDAR. Then, drift angle of the ship was controlled by the propulsion difference of the port and starboard side that based on PID control. The algorithm performance was verified by participating in the 2020 Korea Autonomous BOAT (KABOAT).

• 제어로봇시스템학회논문지
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• 제10권10호
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• pp.940-946
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• 2004

In this paper, an efficient real-time control architecture for autonomous navigation of powered wheelchair is developed. Since an advanced intelligent wheelchair requires real-time performance, the control software architecture of powered wheelchair is developed under Linux real-time extension Real-time Application Interface (RTAI). A hierarchical control structure for autonomous navigation is designed and implemented using real-time processe and interrupts handling of sensory perception based on slanted surface LRF, emergency handling capability, and motor control with 0.1 msec sampling time. The performance of our powered wheelchair system with the implemented control architecture for autonomous navigation is verified via experiments in a corridor.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 춘계학술대회 논문집
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• pp.1355-1359
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• 2004

In this paper, We elicit the necessity of the Autonomous Decentralized Traffic Control System by analyzing problems of the Centralized Traffic Control System and present operation system. The automatic traffic control system using in large and high-density railway stations is designed and implemented on the basis of the elicited necessity in this paper. It is proposed to use broadcasting protocol for interface of stations in order to ensure autonomy. The result is that advantages of the Autonomous Decentralized Traffic Control System makes on-line expansion and maintenance available. step-by-step construction available. and reduce the area of the influences of system fault when any system fault happens.

• 한국군사과학기술학회지
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• 제21권2호
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• pp.204-210
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• 2018

As the 4th industrial revolution and artificial intelligence technology develop, it is expected that there will be a revolutionary changes in the security robot. However, artificial intelligence system requires enormous hardwares for tremendous computing loads, and there are many challenges that need to be addressed more technologically. This paper introduces precise tracking control technique of autonomous system that need to move repetitive paths for security purpose. The input feedforward signal is generated by using the inverse based iterative learning control theory for the 2 input 2 output nonminimum-phase system which was difficult to overcome by the conventional feedback control system. The simulation results of the input signal generation and precision tracking of given path corresponding to the repetition rate of extreme, such as bandwidth of the system, shows the efficacy of suggested techniques and possibility to be used in military security purposes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.595-609
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• 2020

In this study, we propose a decentralized mathematical model for predictive control of a system of multi-autonomous unmanned aerial vehicles (UAVs), also known as drones. Being decentralized and autonomous implies that all members make their own decisions and fly depending on the dynamic information received from other unmanned aircraft in the area. We consider a variety of realistic characteristics, including time delay and communication locality. For this flocking flight, we do not possess control for central data processing or control over each UAV, as each UAV runs its collision avoidance algorithm by itself. The main contribution of this work is a mathematical model for stable group flight even in adverse weather conditions (e.g., heavy wind, rain, etc.) by adding Gaussian noise. Two of our proposed variance control algorithms are presented in this work. One is based on a simple biological imitation from statistical physical modeling, which mimics animal group behavior; the other is an algorithm for cooperatively tracking an object, which aligns the velocities of neighboring agents corresponding to each other. We demonstrate the stability of the control algorithm and its applicability in autonomous multi-drone systems using numerical simulations.

• 품질경영학회지
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• 제46권4호
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• pp.973-982
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• 2018

Purpose: The purpose of this study is to develop an effective simulation modeling formalism for autonomous control systems, such as unmanned aerial vehicles and unmanned surface vehicles. The proposed simulation modeling formalism can be used to evaluate the quality and effectiveness of autonomous control systems. Methods: The proposed simulation modeling formalism is developed by extending the classic DEVS (Discrete Event Systems Specifications) formalism. The main advantages of the classic DEVS formalism includes its rigorous formal definition as well as its support for the specification of discrete event models in a hierarchical and modular manner. Results: Although the classic DEVS formalism has been a popular modeling tool, it has limitations in describing an autonomous control system which needs to make decisions by its own. As a result, we proposed an extended DEVS formalism which enables the effective description of internal decisions according to its conditional variables. Conclusion: The extended DEVS formalism overcomes the limitations of the classic DEVS formalism, and it can be used for the effectiveness simulation of autonomous weapon systems.