• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.357-357
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• 2000

In this study, we consider a multi-input multi-output styrene polymerization reactor system for which the monomer conversion and the weight average molecular weight are controlled by manipulating the jacket inlet temperature and the feed flow rate. The reactor system is identified by using a linear subspace identification method and then the output feedback model predictive controller is constructed on the basis of the identified model. Here we use the Best Linear Unbiased Estimation (BLUE) filter as a stochastic estimator instead of the Kalman filter. The BLUE filter observes the state successfully without any a priori information of initial states. In contrast to the Kalman filter, the BLUE filter eliminates the offset by observing the state of the augmented system regardless of a priori information of the initial state for an integral white noise augmented system. A BLUE filter has a finite impulse response (FIR) structure which utilizes finite measurements and inputs on the most recent time interval [i-N, i] in order to avoid long processing times.

• Smart Structures and Systems
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• v.29 no.4
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• pp.617-624
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• 2022

A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1295-1304
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• 2004

In this paper, the Bayesian recurrent neural network is proposed to predict time series data. A neural network predictor requests proper learning strategy to adjust the network weights, and one needs to prepare for non-linear and non-stationary evolution of network weights. The Bayesian neural network in this paper estimates not the single set of weights but the probability distributions of weights. In other words, the weights vector is set as a state vector of state space method, and its probability distributions are estimated in accordance with the particle filtering process. This approach makes it possible to obtain more exact estimation of the weights. In the aspect of network architecture, it is known that the recurrent feedback structure is superior to the feedforward structure for the problem of time series prediction. Therefore, the recurrent neural network with Bayesian inference, what we call Bayesian recurrent neural network (BRNN), is expected to show higher performance than the normal neural network. To verify the proposed method, the time series data are numerically generated and various kinds of neural network predictor are applied on it in order to be compared. As a result, feedback structure and Bayesian learning are better than feedforward structure and backpropagation learning, respectively. Consequently, it is verified that the Bayesian reccurent neural network shows better a prediction result than the common Bayesian neural network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.647-666
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• 2009

Multiple-input multiple-output (MIMO) multiplexing is an attractive technology that increases the channel capacity without requiring additional spectral resources. The design of low complexity and high performance detection algorithms capable of accurately demultiplexing the transmitted signals is challenging. In this technical survey, we introduce the state-of-the-art MIMO detection techniques. These techniques are divided into three categories, viz. linear detection (LD), decision-feedback detection (DFD), and tree-search detection (TSD). Also, we introduce the lattice basis reduction techniques that obtain a more orthogonal channel matrix over which the detection is done. Detailed discussions on the advantages and drawbacks of each detection algorithm are also introduced. Furthermore, several recent author contributions related to MIMO detection are revisited throughout this survey.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1424-1429
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• 2003

In this paper, the design method of sliding mode control (SMC) system for SISO linear system is discussed. First, we consider the similarity between the design method of sliding mode hyper plane using the strict positive realness and the characteristics of zeros of feedback system and the design method of simple adaptive control. Based on such a consideration, we propose the new design method of SMC system using parallel dynamic compensator. As a result, SMC system can be constructed only with the derivative of output signal for controlled plant. The performance of SMC system designed by proposed method is confirmed through the numerical example.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2291-2294
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• 2003

In this paper, analysis and control design of ac-dc converter, normally nonlinear time-varying system, using sliding mode controller to achieve fast output voltage response, disturbance rejection and robust system in the presence of load variation are demonstrated. The objective of this method is to develop methodology for output voltage to be constant and input current sinusoidal that results in nearly unity power factor, respectively. In addition the converter can be also bidirectional power flow. Simulation results using Matlab/Simulink show the effectiveness of sliding mode control system compared with linear feedback controller to guarantee enhanced PF>0.98, THD<5%, and ripple output voltage is less than 1% at the maximum output power.

• Journal of Communications and Networks
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• v.12 no.5
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• pp.442-448
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• 2010

Cooperative relaying methods have attracted a lot of interest in the past few years. A conventional cooperative relaying scheme has a source, a destination, and a single relay. This cooperative scheme can support one symbol transmission per time slot, and is caned full rate transmission. However, existing fun rate cooperative relay approaches provide asymmetrical gain for different transmitted symbols. In this paper, we propose a cooperative relaying scheme that is assisted with dual relays and provides full transmission rate with the same macro-diversity to each symbol. We also address equalization for the dual relay transmission system in addition to addressing the issues concerning the improvement of system performance in terms of optimal power allocations.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1931_1933
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• 2009

NoC 기반 시스템이 적용되는 설계는 시스템 크기가 커짐에 따라 칩 테스트 문제도 동시에 제기 되고 있다. 이에 따라 NoC 기반의 시스템의 테스트 시간을 줄일 수 있는 internal test 방식의 새로운 BIST(Built-in Self-Test) 구조에 관한 연구를 하였다. 기존의 NoC 기반 시스템의 BIST 테스트 구조는 각각의 router와 core에 BIST logic과 random pattern generator로 LFSR(Linear Feedback Shift Register)을 사용하여 연결하는 individual 방식과 하나의 BIST logic과 LFSR을 사용하여 각각의 router와 core에 병렬로 연결하는 distributed 방식을 사용한다. 이때, LFSR에서 생성된 테스트 벡터가 router에 사용되는 FIFO 메모리를 통과하면서 생기는 테스트 타임 증가를 줄이기 위하여 shift register 형태의 FIFO 메모리를 변경하였다 제안된 방법에서 테스트 커버리지 98%이상을 달성하였고, area overhead면에서 효과를 볼 수 있다.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2815-2817
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• 2005

This paper presents an experiment study on the control of a rotary-type inverted pendulum based on the Takagi-Sugeno (T-S) fuzzy model approach. A sufficient condition for stability of the T-S fuzzy control system is given via linear matrix inequalities (LMIs). State-feedback controllers for sub-systems are designed from the sufficient condition via change of variables which is one of the popular LMI techniques. Experimental results on a rotary-type inverted pendulum control show the feasibility of the T-S fuzzy model-based control method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.552-558
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• 1993

In this paper, control of a planar two-link structurally flexible robotic manipulator executing unconstrained and constrained maneuvers is considered. The dynamic model, which is obtained by using the extended Hamilton's principle and the Galerkin criterion, includes the impact force generated during the transition from unconstrained to constrained segment of the robotic task. A method is presented to obtain the linearized equations of motion in Cartesian space for use in designing the control system. The linear quadratic Gaussian with loop transfer recovery (LQG/LTR) design methodology is exploited to design a robust feedback control system that can handle modeling errors and sensor noise, and operate on Cartesian space trajectory errors. The LQG/LTR compensator together with a feedforward loop is used to control the flexible manipulator. Simulated results are presented for a numerical example.