• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.215-221
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• 2006

This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems such as the structural instability, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control were fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system by employing only single algorithm since the system usually includes multiple nonlinearities. In this paper, a switching Pill is considered for a control of saturation and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between the results of simulation and experiment, and then the switching Pill gains are determined using genetic algorithm with some heuristic approach. The performance of the switching Pill controller for saturation and the dual feedback for backlash control is investigated through the simulation. Finally, it is shown that the implemented control system has good results and can be applied to the real humanoid robot system ISHURO.

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.3
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• pp.9-17
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• 2019

Variable guide vanes(VGVs) that consist of link mechanisms and an actuator system are required for an aircraft gas turbine engine to adjust the incidence angle of stator vanes. In this study, we developed a VGV actuator system for three-stage VGVs with two hydraulic actuators. The requirements for the actuator system were derived by analyzing the link mechanisms and air loads, and a hydraulic power-pack was developed based on these requirements. Through a load test using the actuator test-rig and the application of synchronizing control logic with proper control gains, the actuator system could be developed and verified.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.1 s.104
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• pp.24-38
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• 2006

In this paper, we investigate the design and fabrication of a conical spiral antenna suitable for satellite TT&C applications. The shape of the spiral is optimized using a commercial electromagnetic software for good gain and axial ratio performances over $2.0{\sim}2.3\;GHz$ frequencies. A coaxial infinite balun feeding the spiral is designed using experimental methods. A method for precision fabrication of the spiral is presented. Measurements of the fabricated antenna show satisfactory performances over $2.0{\sim}2.3\;GHz$ such as a reflection coefficient less than -18 dB, a maximum gain greater than 4 dB, a gain greater than 0 dB over angles ${\pm}75^{\circ}$ from the antenna boresight, an axial ratio less than 5 dB over angles ${\pm}90^{\circ}$ from the antenna boresight, a front-back ratio greater than 15 dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.11
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• pp.1701-1713
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• 1993

This paper proposes a simple and highly effective RACMC(Real-time ATM Cell Monitoring and Control) algorithm and the resulting bandwidth gain effects art considered. RACMC algorithm performs usage parameter controls according to the monitoring informations of input data cells generated from the accepted connections and the controlling informations set by the M/P(Management Plane) for that connection. The results of monitoring and controlling actions for ATM data cells are transmitted to the M/P and the control parameters in lookup table are updated according to the condition of currently used bandwith. Therefore, the proposed algorithm can allocate network resource optimally and solve the several tantalizing problems that the existing cell control algorithm have, that is, the difficulty in controlling as monitoring very bursty traffics, unavoidable processing delay, and limited input buffer size when implemented. By the performance analysis using computer simulation, RACMC algorithm proves to be very effective especially in ATM network as implemented simply.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.1
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• pp.1-8
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• 2017

The optimal gain design method of a three-phase boost converter is proposed in this study. The control system has a two-loop configuration, in which each controller is coupled closely; thus, the optimal design is difficult to achieve using conventional gain-tuning method. The proposed method is adopted to the MATLAB SISO TOOL software and is based on the controller requirements, which are phase margin and cut-off frequency of the open-loop system. The optimal proportional -integral gains can be designed easily using the proposed interactive method of the SISO TOOL. The performance of the proposed system is verified through simulation and experiments.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.614-616
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• 2004

It is waste of time in industrial plant that the PI controller gain tuning. The PI controller has many trial-and-error steps for gain design. This paper proposes the optimum gain design of PI controller using a speed estimation in sensorless vector-control. In this method, a degree of stability and Hurwitz theory are applied and the controller gain is expressed by system parameters.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.897-899
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• 1999

This paper presents a scaling factor tuning method to improve the performance of fuzzy logic controller. Tuning rules and reasoning are utilized off-line to determine the scaling factors based on absolute value of the error and its difference. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a dc-servo motor control system. The performance of this control system is demonstrated higher than a conventional fuzzy logic controller(FLC).

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.452-454
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• 1998

Asymmetric cylinders are usually used as an actuator of active suspensions. The conventional optimal controller design does not include actuator dynamics as a state. and force controller is needed to track the desired force. But the actuator is not ideal, so performance of an active suspension system is degraded. In this paper, we take account nonlinear actuator dynamics and obtain a linear model using a feedback linearization technique then apply optimal control method. For real time application, gain-scheduling method is used. Effectiveness of proposed method is demonstrated by numerical simulation of 1/4 car model.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.3
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• pp.134-141
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• 2004

Recently, neural network techniques are widely used in adaptive and learning control schemes for production systems. However, in general it takes up a lot of time to learn in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult for the PID gains suitably, lots of researches have been reported with respect of turning schemes of PID gains. A neural network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed neural network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accidents.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.304-306
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• 2007

In this paper, we presents a scheme for the parameter estimation and optimal control scheme for apparatus of container crane system. For parameter estimation, first, we construct the open loop of the container crane system and estimate its parameters based on input-output data, a real-coded genetic algorithm(RCGA) and the model adjustment technique. The RCGA plays an important role in parameter estimation as an adaptive mechanism. For controller design, state feedback gain matrix is searched by another RCGA and the estimated model. The performance of the proposed methods are demonstrated through a set of simulation and experiments of the experimental apparatus.