• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.59-66
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• 1997

A general procedure for a motion capture and mimic system has been delineated. Utilizing sensors operated in the magnetic fields, complicated and optimized movements are easily digitized to analyze and repreduce. The system consists of a motion capture module, a motion visualization module, a motion plan module, a motion mimic module, and a GUI module. Design concepts of the system are modular, open, and user friendly to ensure the overall system performance. Custom-built and/or off-the-shelf modules are ease- ly integrated into the system. With modifications, this procedure can be applied for complicated motion controls. This procedure is implemented on tracking a head and balancing a pole. A neural controller based on this control scheme dtilizing human motions can easily evolve from a small amount of learning data.

• Proceedings of the Korean Nuclear Society Conference
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• 2005.10a
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• pp.1093-1094
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• 2005

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1997.06c
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• pp.32-40
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• 1997

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.2
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• pp.186-193
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• 2002

A new integrated torque and speed control algorithm has been proposed for the load balancing of rollers in continuous strip processing line(CSPL). Using the proposed method, the output torque and speed can be controlled to follow the reference in spite of nonideal effects such as the speed reference error and/or the controller gain difference between rolls. This new algorithm can be easily implemented in a motor drive system of each roll as it does not require the torque feedback of the others. Through the simulation and experiments for a simple CSPL consists of four driven rolls, the load balancing performance of the proposed scheme is presented and compared with that of conventional method.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.239-247
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• 2017

The purpose of this study is to develop a motion generation technique based on a double inverted pendulum model (DIPM) that learns and reproduces humanoid robot (or virtual human) motions while keeping its balance in a pattern similar to a human. DIPM consists of a cart and two inverted pendulums, connected in a serial. Although the structure resembles human upper- and lower-body, the balancing motion in DIPM is different from the motion that human does. To do this, we use the motion capture data to obtain the reference motion to keep the balance in the existence of external force. By an optimization technique minimizing the difference between the motion of DIPM and the reference motion, control parameters of the proposed method were learned in advance. The learned control parameters are re-used for the control signal of DIPM as input of linear quadratic regulator that generates a similar motion pattern as the reference. In order to verify this, we use virtual human experiments were conducted to generate the motion that naturally balanced.

• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.4
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• pp.332-341
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• 2014

A cascaded H-bridge multi-level STATCOM(STATic synchronous COMpensator), which is composed of many cell inverters with independent dc-sources, generates inevitably dc-side voltage unbalance among phases when it compensates unbalanced load. It comes from the difference of flowing active power in each phase when this compensator makes negative-sequence current to eliminate the unbalance of source-side current. However, this unbalance can be controlled by injecting zero-sequence current which is decoupled with grid currents, so the compensator can work well during this balancing process. Both a feedback control algorithm, which produces zero-sequence current proportional to dc-side voltage unbalance within each phase, and a feedforward control algorithm, which makes zero-sequence current directly from the compensator's negative-sequence current, were proposed. The dc-side voltage of each phase can be controlled stably by these proposed algorithms in both steady-state and transient, so the compensator can have fast response to satisfy control performance under rapid changing load. These balancing controllers were implemented and verified via simulation and experiment.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.2
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• pp.95-101
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• 2017

A simple and practical voltage balance method for a solid-state transformer (SST) is proposed to reduce the voltage difference of cascaded H-bridge converters. The tolerance device components in SST cause the imbalance problem of DC-link voltage in the H-bridge converter. The Max/Min algorithms of voltage balance controller are merged in the controller of an AC/DC rectifier to reduce the voltage difference. The DC-link voltage through each H-bridge converter can be balanced with the proposed control methods. The design and performance of the proposed SST are verified by experimental results using a 30 kW prototype.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.22-29
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• 2007

Two fuzzy controllers defined by 2 input variables cooperate to control a cartpole system in terms of balancing as well as centering. The cooperation is due to the BOXES scheme that selects one of the fuzzy controllers for each time step according to the content of box that is established through the critic of the control action by the fuzzy controllers. It is found that the control scheme is good at controlling the cartpole system so that the system is stabilized fast while the BOXES develops its ability to select proper fuzzy controller through experience.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.531-531
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• 2000

The challenge is to control unstable nonlinear dynamic systems using only sparse feedback from the environment concerning its performance. The design of such controllers can be achieved by evolving neural networks. An evolutionary approach to train neural networks in realtime is proposed. Evolutionary strategies adapt the weights of neural networks and the threshold values of neuron's synapses. The proposed method has been successfully implemented for pole balancing problem.