• 대한기계학회논문집A
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• 제24권3호
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• pp.653-660
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• 2000

The automatization by industrial robot of today is merely rely on to the simple position repeating works, but requirements of research and development to the force control which would adapt positively to various restriction or contacting works to environment. In this paper, a learning control algorithm using, neural networks is proposed for the position and force control by a direct-drive robot. The proposed controller is the feedback controller to which the learning function of neural network is added on to and has a character of improving controller's efficiency by learning. The effectiveness of the proposed algorithm is demonstrated by the experiment on the hybrid position and force control of a parallelogram link robot with a force sensor.

• 로봇학회논문지
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• 제2권3호
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• pp.212-220
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• 2007

This paper proposes a method of avoiding obstacles and tracking a moving object continuously and simultaneously by using new concepts of virtual tow point and fuzzy danger factor for differential wheeled mobile robots. Since differential wheeled mobile robot has smaller degree of freedom to control and are non-holonomic systems, there exist multiple solutions (trajectories) to control and reach a target position. The paper proposes 'fuzzy danger factor' for obstacles avoidance, 'virtual tow point' to solve non-holonomic object tracking control problem for unique solution and three kinds of fuzzy logic controller. The fuzzy logic controller is policy decision controller with fuzzy danger factor to decide which controller's result is more valuable when the mobile robot is tracking a moving object with obstacles to be avoided.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.58-65
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• 2003

In this paper, a new model, which is a Takagi-Sugeno fuzzy model, for mobile robot is presented. A controller, consisting of two loops the one of which is the inner state feedback loop designed for stability and the outer loop is a PI controller designed for tracking the reference input, is suggested. Because the robot dynamics is nonlinear, it requires the controller to be insensitive to the nonlinear term. To achieve this objective, the model is developed by well known T-S fuzzy model. The design algorithm of inner state-feedback loop is regional pole-placement. In this paper, regions, for which poles of the inner state feedback loop are lie in, are formulated by LMI's. By solving these LMI's, we can obtain the state feedback gains for T-S fuzzy system. And this paper shows that the PI controller is equivalent to the state feedback and the cost function for reference tracking is equivalent to the LQ(linear quadratic) cost. By using these properties, it is also shown in this paper that the PI controller can be obtained by solving the LQ problem.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.151-156
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• 1998

In this paper, we present new control method for robot manipulators. The design objective can be the implementation of minimax controller with H$_{\infty}$ performance via LMI approach to guarantee the robustness and to obtain the exact tracking performance for robot manipulators with system parameter uncertainty and exogenous disturbance. We show that the Algebraic Riccati equation (ARE) which is needed for the construction of H$_{\infty}$ controller can be recast into the Algebraic Riccati Inequality (ARI) and the optimal control gain can be obtained by convex optimization method. Then, we will apply the proposed controller to rigid robot manipulators for verifying the performance of our controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 G
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• pp.3024-3026
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• 1999

This paper presents a cooperative action controller of a multi-agent system. To achieve an object, i.e. win a game, it is necessary that a robot has its own roles, actions and work with each other. The presented incorporated action controller consists of the role selection, action selection and execution layer. In the first layer, a fuzzy logic controller is used. Each robot selects its own action and makes its own path trajectory in the second layer. In the third layer, each robot performs their own action based on the velocity information which is sent from main computer. Finally, simulation shows that each robot selects proper roles and incorporates actions by the proposed controller.

• Transactions on Control, Automation and Systems Engineering
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• 제3권4호
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• pp.272-282
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• 2001

Uncertainties are the main reasons of deterioration of contour control of industrial articulated robot arm. In this paper, a high-precision contour control method was proposed to overcome some main uncertainties, such as torque saturation, system delay dynamics, interference between robot links, friction, and so on. Firstly, each considered factor of uncertainties was introduced briefly. Then proper realizable objective trajectory generation was presented to avoid torque saturation from objective trajectory. According to the model of industrial articulated robot arm, construction of Gaussian neural network controller with considering system delay dynamic, interference between robot links and friction was explained in detail. Finally, through the experiment and simulation, the effectiveness of proposed method was verified. Furthermore, based on the results it was shown that the Gaussian neural network controller can be also adapted for the various kinds of friction and high-speed motion of industrial articulated robot arm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.146.2-146
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• 2001

Recently, a need of non-industrial robot, such as service, medical, entertainment and house-keeping robot, has been increased. Therefore, the capability of robot which can do intelligent behavior like interaction with men and its environment become more prominent than the capability of executing simple repetitive task. To implement an intelligent robot which provides intelligent behavior, an effective system architecture including perception, learning, reasoning and action part is necessary. Control architectures for intelligent robot can be divided into two different classes. One is deliberative type controller which is applicate to high level intelligence like environment ...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.622-627
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• 2003

The existing remote control system have some inherent disadvantage of direct control in the limit range. In some special cases, for example, a power apparatus, an unmanned factory, a nuclear factory, a security management system, the tele-operation is needed to control remote robot without limit space. This field is based on the Internet communication. Because the Internet is constructed all over the world. And it is possible that we control remote mobile robot in the long distance. In this paper, we developed a remote control system. This system is divided into two primary parts. These are local site and remote site. There are the moving robot and web server in the remote site and there is the robot control device in local site. The moving robot is moved by two stepper motors and the robot control device consists of SA-1100 micro controller and embedded Linux. And this controller is an embedded system. Public personal computer which is connected the Internet is used for the web server. The web server provides the mobile robot control interface program to the remote controller and captures the image for feedback information. In the whole system, a robot control device is connected with moving robot and web server through the Internet. So the operator can control the moving robot in the distance through the Internet.

• 대한임베디드공학회논문지
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• 제17권2호
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• pp.123-128
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• 2022

This paper proposes a mobile robot platform for education that can experiment with various autonomous driving algorithms such as obstacle avoidance and path planning. The platform consists of a robot module and a remote controller module, both of which are based on the Arduino Nano 33 IoT embedded board. The robot module is designed as a differential drive type using two encoder motors, and the speed of the motor is controlled using PID control. In the case of the remote controller module, a command to control the robot platform is received with a 2-axis joystick input, and an elliptical grid mapping technique is used to convert the joystick input into a linear and angular velocity command of the robot. WiFi and Zigbee are used for communication between the robot module and the remote controller module. The proposed robot platform was tested by measuring and comparing the linear velocity and angular velocity of the actual robot according to the linear velocity and angular velocity commands of the robot generated by the input of the joystick.

• 한국정보통신학회논문지
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• 제18권8호
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• pp.1811-1817
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• 2014

본 논문은 선도 로봇을 추종 로봇이 일정거리와 각도를 두고 추종하는 군집제어에서, 추종 로봇의 질량이 변할 경우, 신경회로망을 통해 보간된 이득을 갖는 PID제어기를 제안한다. 전체 제어시스템은 기구학 제어기와 동역학을 고려한 동적제어기로 구성하였다. 동적제어기는 가변 이득을 가지는 PID 제어기로 구성하여, 추종 로봇의 대표적 질량에 따라 적절한 PID 이득을 유전 알고리즘으로 구하였다. 유전 알고리즘으로 구한 데이터를 기초로 신경회로망을 학습하여 추종 로봇이 임의의 질량을 갖더라도 최적의 PID 이득을 선정할 수 있었다. 모의실험에서 추종 로봇의 질량이 임의의 값으로 변화하는 경우, 신경회로망을 통해 보간된 이득을 갖는 PID 제어기가 고정된 이득을 가지는 PID 제어기에 비해 군집제어에서 추종 성능을 향상시키는 것을 확인하였다.