• Annual Conference of KIPS
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• 2009.11a
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• pp.81-82
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• 2009

본 논문에서는 시각장애인 길 안내 시스템과 같은 다수의 센서를 제어하는 시스템에서 효율적인 디바이스 제어를 위한 쓰레드 구조를 제안한다. 시각장애인의 길안내를 위해 초음파, 적외선 센서, 카메라, GPS, 지자기 센서, 3축 가속도 센서가 사용되며, 이를 효율적으로 제어하기 위해서 각 디바이스마다 각각 쓰레드를 별도로 두며, 뮤텍스 세마포어를 활용해서, 하나의 Zigbee 채널을 공유하기 위한 쓰레드 동기화 기법이 적용된다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.3-6
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• 2000

The magnetic bearing system are intrinsically unstable, and need the feedback control of electromagnetic forces with measured displacements. So the controller design plays an important role in constructing high performance magnetic bearing system. In case of magnetic bearing system, the order of identified model is high because of unknown dynamics included in closed loop systems - such as sensor dynamics, actuator dynamics - and non-linearity of magnetic bearings itself. In this paper the identification and robust control of flexible rotor supported by magnetic bearing are discussed. We measure and identify overall system that contains not only flexible rotor model but also magnetic bearing and time delay. The structured and unstructured uncertainties are modeled that cover variations of natural frequencies, uncertainties in sensor and actuator gains and unmodeled dynamics. And desired performances are specified with several weighting function. Using augmented system that includes identified model, uncertainties, and weighting functions, μ-synthesis is applied to flexible rotor supported with magnetic bearing. The flexible rotor was spin up over the first flexible critical speed.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.609-614
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• 2014

Cerebellar ataxia is a steadily progressive neurodegenerative disease associated with loss of motor control, leaving patients unable to walk, talk, or perform activities of daily living. Direct motor instruction in cerebella ataxia patients has limited effectiveness, presumably because an inappropriate closed-loop cerebellar response to the inevitable observed error confounds motor learning mechanisms. Recent studies have validated the age-old technique of employing motor imagery training (mental rehearsal of a movement) to boost motor performance in athletes, much as a champion downhill skier visualizes the course prior to embarking on a run. Could the use of EEG based BCI provide advanced biofeedback to improve motor imagery and provide a "backdoor" to improving motor performance in ataxia patients? In order to determine the feasibility of using EEG-based BCI control in this population, we compare the ability to modulate mu-band power (8-12 Hz) by performing a cued motor imagery task in an ataxia patient and healthy control.