• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.787-792
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• 1991

This paper proposes a steering control algorithm for non-holonomic mobile robots. The steering control algorithm is essential to navigate autonomous vehicles which employ comination of the dead reckoning and absolute sensor system such as a machine vison for detecting landmarks in order to estimate the current location of the mobile robot. The proposed algorithm is based on the minimum time BANG-BANG controller and curvature-continuity curve design method. In the BANG-BANG control scheme we introduce velocity/acceleration limiter to avoid any slippage of driving wheels. The proposed scheme is robot-independent and hence can be applied to various kinds of mobile robot or vehicles. To show the effectness of the proposed control algorithm, a series of computer simulations were conducted for two-wheel driven mobile robot.

• 한국항행학회논문지
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• 제20권3호
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• pp.226-231
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• 2016

이동로봇의 제어는 로봇 분야에 있어 중요한 이슈이다. 이동로봇의 자율주행은 다양한 작업 환경에서 중시되고 있다. 자율 주행을 위해 이동로봇은 장애물을 감지, 회피하며 지능시스템을 도입한 제어 방식들을 사용해 충돌회피의 성능을 보완하는 연구가 활발히 진행되고 있다. 본 논문에서는 이동 로봇의 기구학적 모델을 분석하고 조향각 제어를 위한 type-2 fuzzy self-tuning PID 제어기를 설계하였다. Type-2 fuzzy 제어기는 type-1 fuzzy 제어기와 달리 복수 개의 값을 가지므로 언어표현의 모호함의 자유도가 높다. 본 논문에서는 설계된 제어기와 기존의 PID 제어기, type-1 fuzzy self-tuning PID 제어기를 비교하기 위한 방법으로 MATLAB Simulink를 사용하여 시뮬레이션을 하였다. 시뮬레이션 비교 결과 기존의 PID제어기와 type-1 fuzzy self-tuning PID 제어기의 성능보다 type-2 fuzzy self-tuning PID 제어기의 성능이 우수하다는 것을 확인하였다.

• 농업과학연구
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• 제50권4호
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• pp.773-784
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• 2023

In this study, we developed a dynamic model and steering controller model for an autonomous tractor and evaluated their performance. The traction force was measured using a 6-component load cell, and the rotational speed of the wheels was monitored using proximity sensors installed on the axles. Torque sensors were employed to measure the axle torque. The PI (proportional integral) controller's coefficients were determined using the trial-error method. The coefficient of the P varied in the range of 0.1 - 0.5 and the I coefficient was determined in 3 increments of 0.01, 0.05, and 0.1. To validate the simulation model, we conducted RMS (root mean square) comparisons between the measured data of axle torque and the simulation results. The performance of the steering controller model was evaluated by analyzing the damping ratio calculated with the first and second overshoots. The average front and rear axle torque ranged from 3.29 - 3.44 and 6.98 - 7.41 kNm, respectively. The average rotational speed of the wheel ranged from 29.21 - 30.55 rpm at the front, and from 21.46 - 21.63 rpm at the rear. The steering controller model exhibited the most stable control performance when the coefficients of P and I were set at 0.5 and 0.01, respectively. The RMS analysis of the axle torque results indicated that the left and right wheel errors were approximately 1.52% and 2.61% (at front) and 7.45% and 7.28% (at rear), respectively.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 춘계학술대회
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• pp.468-469
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• 2018

본 연구는 자동차 조향제어 시스템에 적용 가능한 CNN(Convolutional Neural Network)을 설계하고자 한다. CNN은 현재 많은 분야에서 폭넓게 사용되고 있으며, 특히 영상 분류(image classification) 작업에 있어 매우 뛰어난 성능을 나타내고 있다. 그러나 이러한 CNN이 함수를 근사하는 회귀(regression) 문제에서는 많이 적용되지 못하고 있다. 이는 CNN의 입력으로 이미지 데이터와 같은 다차원적인 데이터 구조로 되어 있어 일반적인 제어 시스템의 적용이 쉽지 않기 때문이다. 최근 들어 자율주행차에 관해 연구가 활발히 진행되고 있으며, 자율주행차를 구현하기 위해 많은 기술이 요구된다. 이를 위해 차량에 장착된 블랙박스의 영상 이미지를 사용하여 차선을 검출하고 검출된 차선에 따라 소실점 등을 검출하여 자율주행차를 제어하는 연구가 많이 진행되었다. 그러나 소실점 검출에 있어 영상 이미지의 외부 환경, 순간적인 차선의 소실 그리고 반대편 차선의 검출 등 여러 요인으로 인하여 안정적인 소실점 검출에 어려움이 있다. 본 연구에서는 자동차에서 촬영된 블랙박스 영상 이미지를 입력받아 자율주행차의 조향제어를 위해 CNN을 적용해 보고자 한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.151-151
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• 2000

The objective of this paper is to develop the new robust and adaptive control system against external environments as applying the probabilistic recognition which is one of the inherent properties of immune system, ability of learning and memorization, and regulation theory of immune network to the system under engineering point of view. In this paper, HIA(Humoral Immune Algorithm) PID controller using Neural Network Identifier was proposed to drive the autonomous guided vehicle(AGV) more effectively. To verify the performance of the proposed HIA PID controller, some experiments for the control of steering and speed of that AGV are performed.

• 융합신호처리학회논문지
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• 제4권1호
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• pp.56-63
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• 2003

본 논문은 실제 무인주행자동차에 적용할 수 있는 비전 기반의 소형 자율이동로봇 개발에 관한 연구를 제시한다. 이전의 자율주행차량은 하드웨어 설계의 복잡성, 실장의 어려움과 많은 계산량으로 인해 PC에 대한 의존도가 높았다. 본 논문에서는 고속에서 정확한 조향 및 빠른 이동을 할 수 있고, 단일 카메라를 사용한 독립형 시스템으로 지능적 인식을 할 수 있는 소형 자율이동로봇을 제안한다. 제안된 시스템은 폭 25~30cm, 총길이 200cm로 만들어진 트랙에서 실험하였다. 실험 로봇은 직선 트랙에서 평균 32.9km/h, 곡률반경 30~40m인 곡선트랙에서 평균 22.3km/h의 속도로 주행할 수 있었다 이 시스템은 실제 무인 자동차를 쉽게 만들기 위해 사용할 수 있는 차선 인식 알고리즘을 적용한 소형 자율이동로봇 시스템에 대한 하나의 모델을 제시할 수 있었다.

• 한국해양공학회지
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• 제20권6호
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• pp.7-17
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• 2006

Depth and heading control of an AUV are considered to follow the predetermined depth and heading angle. The proposed control algorithm is designed. based on a sliding mode control using estimated hydrodynamic coefficients. The hydrodynamic coefficients are estimated with conventional nonlinear observer techniques, such as sliding mode observer and extended Kalman filter. By using the estimated coefficients, a sliding mode controller is constructed for the combined diving and steering maneuver. The simulation results of the proposed control system are compared with those of control system with true coefficients. This paper demonstrates the proposed control system, discusses the mechanisms that make the system stable and follows the desired depth and heading angle, accurately, in the presence of parameter uncertainty.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 추계학술대회 논문집
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• pp.180-185
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• 2004

This paper shows how can be controlled the rubber tired TRAM by electromagnetic field with a specific pattern as autonomous driving system. The system is composed with drive elements. steering elements. navigational devices. transmitter/receivers and sensor means for sensing the position relative to the magnetic markers. There are difficulties in sensing track conditions. curvatures. slops etc. forward compared to that of the control system optically. The sensing track conditions previously is important for running stability and riding comfort. This paper shows how can achieve track condition in advance by means of electromagnetic pattern originally.

• 제어로봇시스템학회논문지
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• 제12권9호
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• pp.850-855
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• 2006

This is concerned with the development and design of automatic maneuvering system using Differential Global Positioning System(DGPS). To achievement of autonomous maneuvering controller for giant ship, first, we investigated automatic maneuvering controller using DGPS in motor car. The sensors are configured with DGPS and digital compass. We calculated velocity and steering angle of motor car based on sensor signal. To design the controller, we derived the bicycle model and developed critically damped controller. The critically damped controller can be tracing previously appointed position in the fastest time. We are used a laptop computer to realize and the control algorithm is programmed by visual basic software. The obtained experimental results from developed system show unmanned motor car is good tracing planed positions. Hence, the system is looking forward to use the autonomous maneuvering control fur giant ship.

• 제어로봇시스템학회논문지
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• 제21권3호
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• pp.199-209
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• 2015

This paper presents a model predictive control (MPC) approach to control the steering angle in an autonomous vehicle. In designing a highly automated driving control algorithm, one of the research issues is to cope with probable risky situations for enhancement of safety. While human drivers maneuver the vehicle, they determine the appropriate steering angle and acceleration based on the predictable trajectories of surrounding vehicles. Likewise, it is required that the automated driving control algorithm should determine the desired steering angle and acceleration with the consideration of not only the current states of surrounding vehicles but also their predictable behaviors. Then, in order to guarantee safety to the possible change of traffic situation surrounding the subject vehicle during a finite time-horizon, we define a safe driving envelope with the consideration of probable risky behaviors among the predicted probable behaviors of surrounding vehicles over a finite prediction horizon. For the control of the vehicle while satisfying the safe driving envelope and system constraints over a finite prediction horizon, a MPC approach is used in this research. At each time step, MPC based controller computes the desired steering angle to keep the subject vehicle in the safe driving envelope over a finite prediction horizon. Simulation and experimental tests show the effectiveness of the proposed algorithm.