• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.178.3-178
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• 2001

This paper is concerned with designing a neural network based navigator that is optimized in a user-defined sense for a mobile robot using ultrasonic sensors to travel to a goal position safely and efficiently without any prior map of the environment. The neural network has a dynamically reconfigurable structure that not only can optimize the weights but also the input sensory connectivity in order to meet any user-defined objective. Therefore, in this research, we can select an optimal subset of sensory inputs that results in the best performance related to both navigation and structural complexity. Further, this research uses the manually trained initial population and the modular neural network to alleviate ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.127.1-127
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• 2001

In this paper we propose an input/output model based fault diagnosis method to detect and isolate single faults in the robot arm control system. The proposed algorithm is functionally composed of three main parts-parameter estimation, fault detection, and isolation, When a change in the system occurs, the errors between the system output and the estimated output cross a predetermined threshold, and once a fault in the system is detected, and in this zone the estimated parameters are transferred to the fault classifier by ART2(adaptive resonance theory 2) neural network for fault isolation. Since ART2 neural network is an unsupervised neural network fault classifier does not require the knowledge of all possible faults to isolate the faults occurred in the system. Simulations are carried out to evaluate the performance of the proposed ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.102.3-102
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• 2001

In this paper, we propose a novel method that can detect face region effectively with fuzzy theory and neural network We make fuzzy rules and membership functions to describe the face color. In this algorithm, we use a perceptually uniform color space to increase the accuracy and stableness of the nonlinear color information. We use this model to extract the face candidate, and then scan it with the pre-built sliding window by using a neural network-based pattern-matching method to find eye. A neural network examines small windows of face candidate, and decides whether each window contains eye. We can standardize the face candidate geometrically with detected eyes.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.120.4-120
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• 2002

$\textbullet$ In order to operate EP actuator, high voltage is applied to that. $\textbullet$ Our previous control algorithm for an EP actuator was PI method with constant gain. $\textbullet$ But this Control method is limitation such as rising time, steady-state error, and settling time. $\textbullet$ A neural network algorithm is proposed for improvement of performance. $\textbullet$ To do this, neural network algorithm changes the gain of PI control. $\textbullet$ In order to efficient drive EP actuator, the gain is changed at some point. $\textbullet$ Neural network method improve the performance of operation.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.728-733
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• 2009

This paper presents the compensation of mechanical deflection error in SCARA robot. End of robot gripper is deflected by weight of arm and pay-load. If end of robot gripper is deflected constantly regardless of robot configuration, it is not necessary to consider above mechanical deflection error. However, deflection in end of gripper varies because that moment of each axis varies when robot moves, it affects the relative accuracy. I propose the compensation method of deflection error using neural network. FEM analysis to obtain the deflection of gripper end was carried out on various joint angle, the results is used in neural network teaming. The result by simulation showed that maximum relative accuracy reduced maximum 9.48% on a given working area.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.5
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• pp.94-98
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• 2012

Butterfly valves are usually used by the plumbing systems in plant engineering field. Valves are used for controlling the flow rate and pressure of fluid. In order to control the flow rate using butterfly valve, the position control of valve disc should be designed. However, since there are lots of uncertain disturbance in plumbing system, the robust control system should be considered. Therefore, the sliding mode control system using neural network algorithm is proposed in this paper. The proposed control system provides the estimating method using neural network for the unmeasurable disturbance in the plumbing system. The performance of the proposed control system is evaluated through computer simulations.

• 한국가시화정보학회:학술대회논문집
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• 2004.11a
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• pp.52-55
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• 2004

Thermo-chromic Liquid Crystal(TLC) particles were used as temperature sensor for thermal fluid flow. $1K\times1K$ CCD color camera and Xenon Lamp(500W) were used for the visualization of a Hele-Shaw cell. The characteristic between the reflected colors from the TLC and their corresponding temperature shows strong non-linearity. A neural network known as having strong mapping capability for non-linearity is adopted to quantify the temperature field using the image of the flow. Improvements of color-to-temperature mapping was attained by using the local color luminance (Y) and hue (H) information as the inputs for the constructed neural network.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.7
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• pp.955-960
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• 2004

In this paper, a neural network controller that can be implemented in parallel with a PD controller is suggested for motion control of a hydraulic servo cylinder. By applying a self-excited oscillation method, the system design parameters of open loop transfer function of servo cylinder system are identified. Based on system design parameters, the PD gains are determined for the desired closed loop characteristics. The Neural Network is incorporated with PD control in order to compensate the inherent nonlinearities of hydraulic servo system. As an application example, a motion control using PD-NN has been performed and proved its superior performance by comparing with that of a PD control.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.29-38
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• 1997

A closed-loop system modeling of an active/semiactive suspension system has been accomplished through an artificial neural network. A 7DOF full model as a system's equation of motion has been derived and an output feedback linear quadratic regulator has been designed for control purpose. A training set of a sample data has been obtained through a computer simulation. A 7DOF full model with LQR controller simulated under several road conditions such as sinusoidal bumps and rectangular bumps. A general multilayer perceptron neural network is used for dynamic modeling and target outputs are fedback to the a layer. A backpropagation method is used as a training algorithm. Model validation of new dataset have been shown through computer simulations.