• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1679-1683
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• 2005

This paper suggests the new type of a joint torque sensor which is attached at each joint of a manipulator for making compliance. Previous six axis force/torque sensors are high cost and installed end-effector of the manipulator. However, torque on links of previous an end-effector cannot be measured. We design a joint torque sensor that can be fully integrated with an actuator in order to measure applying torque of the manipulator. The sensor system is designed through the structural analysis. The proposed joint torque sensors are installed to the 6 DOF manipulator of a mobile robot for hazardous works and we implemented experiments of measuring applied torque to the manipulator. By the experiment, we proved that the proposed low-cost joint torque sensor gives acceptable performance when we control a manipulator.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.220-226
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• 2002

In this paper, we develop the intelligent digitally redesigned fuzzy controller for nonlinear systems. Takagi-Sugeno (TS) fuzzy model is used to model the nonlinear systems and a continuous-time fuzzy-model-based controller is designed based on the extended parallel-distributed-compensation(EPDC) method . The digital controllers are determined from existing analogue controllers. The proposed method provides an accurate and effective method for digital control of continuous-time nonlinear systems and enables us to efficiently implement a digital controller via the pre-determined continuous-time 75 fuzzy-model-based controller. We have applied the proposed method to the duffing forced oscillation system to show the effectiveness and feasibility of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.45-49
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• 1997

In this paper, we controlled a Rotary Inverted Pendulum System using Neuro-Fuzzy Controller(NFC). The inverted pendulum system is widely used as a typical example of an unstable nonlinear control system which is difficult to control. Fuzzy theory have been because membership functions and rules of a fuzzy controller are often given by experts or a fuzzy logic control system. This controller is a feedforward multilayered network which integrates the basic elements and functions of a tradtional fuzzy logic controller into a connectionist structure which has distributed learning abilities. Such NFC can be constructed from training examples by learning rule, and the structure can be trained to develop fuzzy logic rules and find optimal input/output membership functions. Using this controller, we presented the results that controlled a Rotary Inverted Pendulum System and the associated algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.165-168
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• 1999

The support or automation of various kinds of intelligent work is urged at large, integrated control centers. Given this demand, a decision making system for wash timing of polluted insulators, applying the Bayesian rule theory, has been developed in order to support maintenance work in the power system. The results of this system application revealed that exact wash timing of the insulators could be determined automatically, equivalent in precision to judgement by skilled operators, thus contributing to further work efficiency.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.104-104
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• 2000

Among durability tests, the accelerated durability test has been widely used to evaluate the durability of vehicle structure and chassis pans in a shon period of time on the designed road which has severe surface conditions. However it increases the drivers fatigue mainly caused by the severe driving conditions. The drivers difficulty of maintaining constant speed and controlling the steering wheel reduces the reliability of test results. The durability test includes the position and distance sensing system for the recognition of the absolute and relative driving position, the driving control system for the control of whole driving circumstance, the emergency system for responding to system errors. AGVDS (Autonomous Guided Vehicle Driving System) was Proved to facilitate the development of now car projects. Therefore the AGVDS we propose will help make the fundamentals for all future traffic systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.43-48
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• 2010

This article presents the experimental studies of controlling angle and position of the inverted pendulum system using neural network to compensate for errors caused due to fuzzy controller. Although fuzzy control method can deal with nonlinearities of the system, fixed fuzzy rules may not work and result in tracking errors in some cases. First, a nominal Takagi-Sugeno (TS) type fuzzy controller with fixed weights is used for controlling the inverted pendulum system. Then the neural network is added at the reference input to form the reference compensation technique (RCT)control structure. Neural network modifies the input trajectories to improve system performances by updating internal weights in on-line fashion. The back-propagation learning algorithm for neural network is derived and used to update weights. Control hardware of a DSP 6713 board to have real time control is implemented. Experimental results of controlling inverted pendulum system are conducted and performances are compared.

• Smart Structures and Systems
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• v.19 no.6
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• pp.587-599
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• 2017

This paper introduces an approach to the realization of an ICT-based bridge remote monitoring system that enables real-time monitoring and controlled adjustments for unexpected heavy loads and also for damaging earthquakes or typhoons. In this paper, an integrated bridge remote monitoring system called the "Intelligent Bridge", which consists of a stand-alone monitoring system (SMS) and a web-based Internet monitoring system(IMS), was developed for not only bridge maintenance but also as an application for a para-stressing bridge system. To verify the possibility of controlling the actual structural performance of an "Intelligent Bridge", a model 2-span continuous cable-stayed bridge with adjustable cables was constructed. The experimental results demonstrate that the implemented monitoring system supplies detailed and accurate information about bridge behaviour for further evaluation and diagnosis, and it also opens up prospects for future application of a web-based remote system to actually adjust in-service bridges under field conditions.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.55-67
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• 2004

In this paper, an active vibration control of a translating steel strip in a zinc galvanizing line is investigated. The control objectives in the galvanizing line are to improve the uniformity of the zinc deposit on the strip surfaces and to reduce the zinc consumption. The translating steel strip is modeled as a moving belt equation by using Hamilton’s principle for systems with moving mass. The total mechanical energy of the strip is considered to be a Lyapunov function candidate. A nonlinear boundary control law that assures the exponential stability of the closed loop system is derived. The existence of a closed-loop solution is shown by proving that the closed-loop dynamics is dissipative. Simulation results are provided.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.443-446
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• 2003

Conventional disturbance rejection methods have to derive the inverse model of a system. However, the inverse model of n nonholonomic system is not unique, because an inverse it changes depending on initial conditions and desired values. A kind of internal model control (IMC) using feedback error learning is discussed for the motion control of nonholonomic mobile robots in this paper, The present method is different from a conventional IMC whose control system consists of an inverse model, a direct model and a filter. The present disturbance rejection method need not use a direct model, where the remaining two elements are composed of the same inverse model based on neural networks.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.325-327
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• 2007

In this paper, we implement the internet- based remote control system for intelligent robot. For remote control of the robot, it uses the socket communication of the TCP/IP. It consists of- the user interface and the robot control interface. Robot control interface transmits the navigation and environmental informations of the robot into the user interface. In order to transmit the large environmental images, a JPEG compression algorithm is used. User interface displays the navigation status of the robot and transmits the navigation order into the robot control interface. Also, we propose the design method of the fuzzy controller using navigation data acquired by expert's knowledge or experience. To do this, we use virus-evolutionary genetic algorithm(VEGA). Finally, we have shown the proposed system can be operated through the real world experimentations.