• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.201-202
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• 2020

본 논문에서는 이륜 자동 균형 로봇을 제작하는데 초점을 맞추고 있다. 키워드는 아두이노와 PID컨트롤이다. 아두이노를 사용하여 로봇을 전체적으로 제어하였고 PID컨트롤로 로봇이 스스로 균형을 잡을 수 있도록 한다. 두 바퀴를 이용해 넘어지지 않고, 밸런스를 잡을 수 있도록 로봇의 바퀴, 프레임, 스텝모터, 드라이버 등을 구성하였고, 향후 이륜 자동 균형 로봇이 자유롭게 움직일 수 있도록 PID 정밀 제어를 하게 될 것이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.1065-1066
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• 2015

자동차의 수요가 폭발적으로 늘어났으며, 늘어난 자동차 대수를 고려하여 자동차 검사소 또한 많이 늘어났다. 그러나 최근에는 낮은 유지비용과 이동의 편의성으로 인하여 이륜자동차의 수요가 지속적으로 증가하고 있다. 이륜자동차의 경우 검사제도의 미비로 인하여 대기환경오염 및 불법개조로 인한 여러 가지 사회적 문제가 발생하고 있다. 이러한 이유로 최근에는 이륜자동차의 체계적 관리를 통하여 불법개조를 단속하고, 배기가스 오염물질에 의한 대기오염 및 이륜자동차 소음관리를 위하여 이륜자동차에 대한 검사 제도가 더욱 강화되고 있다. 본 논문에서는 중고차 성능점검 시스템 및 기능종합진단 시스템의 아키텍처를 통하여 이륜자동차에 적용되는 종합관리시스템 적용될 수 있는 통신 프로토콜을 분석하고 개발에 필요한 중요한 설계요소를 제시하고자 한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.16-22
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• 2016

The research on two-wheeled inverted pendulum (TWIP) mobile robots has been ongoing in a number of robotic laboratories around the world. In this paper, we consider a robust controller design for the TWIP mobile robot driving on uniform slopes. We use a 2 degree-of-freedom (DOF) model which is obtained by restricting the spinning motion in a 3 DOF motion dynamic equation. In order to design the robust controller guaranteeing stability of the TWIP mobile robot driving on inclined surface, we propose a sliding mode control based on the theory of variable structure systems and design a sliding surface using the theory of the linear quadratic regulation (LQR). For simulation, the dynamic model of the TWIP mobile robot is constructed using Mathworks' Simulink and the sliding mode control is also implemented using Simulink. From simulation results, we show that the proposed controller effectively controls the TWIP mobile robot driving on slopes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.432-439
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• 2012

In this paper, instead of the conventional PD controller for balancing control of two wheeled inverted pendulum robots, an improved PD controller using the neural network is proposed and implemented for performance verification. First, a two wheeled inverted pendulum robot system is constructed for experiment. Next proper gains of the conventional PD controller according to users' weights are obtained for balancing the robot by use of the trial and error method. The PD gains based on the trial and error method are generalized through the neural network. Experiment results show that the PD controller based on the neural network has better performance than the conventional PD controller.

• Journal of Power System Engineering
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• v.10 no.4
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• pp.172-180
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• 2006

본 논문은 Dijkstra 알고리즘에 기초한 최단거리 경로계획을 하며 이 경로를 추적하기 위한 슬라이딩 모드 제어를 제시한다. 슬라이딩 모드 제어기는 동적매개변수 불확실성과 입력외란이 존재 시에도 강인 점근적으로 계획된 경로를 추적하도록 한다. 더불어 작업장 내의 이동로봇의 위치를 USB 카메라에 의해 감지하며, Pin-hole 카메라모델로 하여 카메라에 의해 관측되는 작업장 내의 이륜구동로봇의 위치좌표를 결정하였으며, 이 위치를 정확히 감지하기 위해 Tsai법을 사용하여 카메라 보정한다. 시뮬레이션 결과는 슬라이딩 모드 제어기의 성능을 검증하기 위해 보였다.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.2
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• pp.162-172
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• 2011

This paper proposes embedded System of two wheeled inverted pendulum robot designed by model based design method, using MATLAB/SIMULINK and LEGO NXT Mindstorms. At first, stability and performance of controller is verified through modeling and simulation. After that direct conversion from simulation model to C code is carried and effectiveness of controller is experimentally verified. Two wheeled inverted pendulum robot has basic function about autonomous balancing control using principle of inverted pedulum and it is also possible to arrive at destination. In this paper, state feedback controller designed by quadratic optimal control method is used. And quadratic optimal control uses state feedback control gain K to minimize performance index function J. Because it is easy to find gain, this control method can be used in the controller of two wheeled inverted pendulum robot. This proposed robot system is experimentally verified with following performances - balancing control, disturbance rejection, remote control, line following and obstacle avoidance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.228-236
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• 2012

In this paper, a controller for two wheeled inverted pendulum robot is designed to have more stable balancing capability than conventional controller. Fuzzy control structure is chosen for the two wheeled inverted pendulum robot, and fuzzy membership function factors for the controller are obtained for specified 3 users' weights using trial-and-error method. Next a neural network is employed to generate fuzzy membership function factors for more stable control performance when the user's weight is arbitrarily selected. Through the simulation study we find that the designed fuzzy controller using the neural network is superior to the conventional fuzzy controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.23-29
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• 2016

This paper presents balancing control of a two-wheel mobile robot (TWMR). TWMR is aimed to maintain balance while moving. Although TWMR can be controlled by linear controllers such as PD controller, time-delayed controller is employed for robustness. Performances of PD controllers and time-delayed controllers are compared. Especially, experimental studies on different acceleration estimation for the time-delayed controller are conducted. Performances by different acceleration estimations of the balancing angle, of the position, and of both angle and position are compared empirically.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.536-544
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• 2011

In this paper, a controller for two wheeled inverted pendulum type robot is designed to have more stable balancing capability than conventional controllers. Traditional PID control structure is chosen for the two wheeled inverted pendulum type robot, and proper gains for the controller are obtained for specified user's weights using trial-and-error methods. Next a neural network is employed to generate PID controller gains for more stable control performance when the user's weight is arbitrarily selected. Through simulation studies we find that the designed controller using the neural network is superior to the conventional PID controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.8-14
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• 2013

In this paper, a control system for two wheeled inverted pendulum robot is implemented to have more stable balancing capability than the conventional control system. Fuzzy control structure is chosen for the two wheeled inverted pendulum robot, and fuzzy membership function factors for the control system are obtained for 3 specified weights using a trial-and-error method. Next a neural network is employed to generate fuzzy membership function factors for more stable control performance when the weight is arbitrarily selected. Through some experiments, we find that the proposed fuzzy control system using the neural network is superior to the conventional fuzzy control system.