• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.248-255
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• 2000

Whereas the linear PID controller is widely used for control of industrial servo systems a high precision positioning system is not easy to control only with the PID controller due to uncertain nonlinear dynamics such as friction backlash etc. As a viable means to overcome the difficulty a learning control scheme is proposed in this paper that is simple and straightforward to implement. The proposed learning controller takes full advantage of current feedback capability of the inner-loop of the control system in that electrical motor dynamics as the well as mechanical part of X-Y positioning system is included in the learning control scheme, The experimental results are given to demonstrate its feasibility and effectiveness in terms of convergence precision of tracking and robustness in comparison with the conventional control method.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.263-272
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• 2000

In this paper we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastcic approximation method it is regarded as a stochastic recursive filter algorithm. In addition we provide a filtering and control condition for a stochastic nonlinear system called the perfect filtering condition in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable and the proposed neural controller is more efficient than the conventional LQG controller and the canonical LQ-Neural controller.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.311-315
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• 2006

Viterbi decoder는 크게 BM(Branch metric), ACS(Add-Compare-Select), SM(Survivor Memory) block 으로 구성되어 있다. 이중 ACSU 부분은 고속 데이터 처리를 위한 bottleneck이 되어 왔으며, 이의 해결을 위한 많은 연구가 활발히 진행되어 왔다. look ahead technique은 ACSU를 M-step으로 처리하고 CS(Carry save) number를 사용한 새로운 비교 알고리즘을 제안하여 high throughput을 추구했으며, minimized method는 block processing 방식으로 forward, backward 방향으로 decoding을 수행하여 ACSU 부분의 feedback을 완전히 제거하여 exteremely high throughput 을 추구하고 있다. 이에 대해 look ahead technique 의 기본 PE(Processing Element)를 바탕으로 minimized method 알고 리즘의 core block 을 bit-level 로 구현하였으며 : code converter 를 이용하여 CS number 가운데 redundat number(l)를 제거하여 비교기를 더 간단히 하였다. SYNOPSYS의 Design compiler 와 TSMC 0.18 um library 를 이용하여 합성하였다.

• Smart Structures and Systems
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• v.6 no.3
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• pp.211-223
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• 2010

Accurate sensing of mechanical strains in civil structures is critical for optimizing structure reliability and lifetime. For instance, combined with intelligent control systems, electromechanical sensor output feedback has the potential to be employed for nondestructive damage evaluation. Application of Ionic Polymer Transducers (IPTs) represents a relatively new sensing approach with more than an order of magnitude higher sensitivity than traditional piezoelectric sensors. The primary reason this sensor has not been widely used to date is an inadequate understanding of the physics responsible for IPT sensing. This paper presents models and experiments defending the hypothesis of a streaming potential sensing mechanism.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.8
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• pp.42-45
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• 2002

A low power SDRAM output buffer with reduced power line noise and feedthrough current is presented. In multi I/O SDRAM output buffer, feedthrough current as well as the corresponding power dissipation are reduced utilizing proposed undershoot protection circuits. Ground bounce is minimized by the pull down driver using intelligent feedback scheme. Ground bounce noise is reduced by 66.3% and instantaneous and average power are reduced by 27.5% and 11.4%, respectively.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.2
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• pp.73-79
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• 2005

This paper is proposed hybrid artificial intelligent (HAI) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using a closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1732-1733
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• 2007

본 연구는 지능알고리즘을 이용하여 비선형궤환을 구현하여 비선형시스템을 선형제어이론으로 제어할 수 있는 가능성을 제시한다. 기존의 비선형 궤환 선형화 이론은 비선형계통에 대한 정확한 모델링을 바탕으로 선형화기법을 적용하여 선형제어이론의 적용을 가능케 하는 것이었으나 본연구는 가상의 선형시스템과 SVM을 사용하여 동특성을 알려지지 않은 계통에 대해서도 적용시킬 수 있는 비선형 궤환선형화 기법의 가능성을 제공한다.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.478-491
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• 2019

This work develops a monitoring system for the population with health concerns. A belt integrated with an on-body circuit and sensors measures a wearer's selected vital signals. The electrocardiogram sensors monitor heart conditions and an accelerometer assesses the level of physical activity. Sensed signals are transmitted to the circuit module through digital yarns and are forwarded to a mobile device via Bluetooth. An interactive application, installed on the mobile device, is used to process the received signals and provide users with real-time feedback about their status. Persuasive functions are designed and implemented in the interactive application to encourage users' physical activity. Two signal processing algorithms are developed to analyze the data regarding heart and activity. A user study is conducted to evaluate the performance and usability of the developed system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.451-452
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• 2021

본 논문에서는 머신러닝의 원리를 쉽게 이해할 수 있는 블록 기반 코딩 플랫폼을 내장한 LMS를 제안한다. 해당 LMS는 Moodle이라는 LMS 플랫폼을 기반으로 사이트가 구축되었으며, LTI를 통해 LMS 내부에 DIY라는 코딩 툴을 내장 시켰다. 또한, 사용자의 모든 로그데이터를 통해 추천시스템을 구상하였으며, DIY를 통해 실행되는 코드를 Python Pedal라이브러리를 백엔드에서 실행 시켜 사용자가 작성한 코드에 대해 즉각적인 피드백을 제공하게 구성되어 있다.

• 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.