• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.165-170
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• 2017

This paper presents an event-triggered model predictive controller for adaptive cruise control system with sampled and quantized-data. Unlike existing works, a longitudinal continuous-time model is used for the predictive control of the system. To efficiently utilize network resources, event-trigger scheme is employed, which allows limited sensor and actuator signal satisfying the condition that the measurement of errors is over the ratio of a trigger level. The proposed control gain is obtained by solving a convex problem satisfying several linear matrix inequalities at every sampling times. Simulation results are given to show the effectiveness of the proposed design method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1491-1497
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• 2007

This paper considers robust and non-fragile guaranteed cost controller design method for descriptor systems with parameter uncertainties and time delay, and static state feedback controller with gain variations. The existence condition of controller, the design method of controller, the upper bound to minimize guaranteed cost function, and the measure of non-fragility in controller are proposed using linear matrix inequality (LMI) technique, which can be solved efficiently by convex optimization. Therefore, the presented robust and non-fragile guaranteed cost controller guarantees the asymptotic stability and non-fragility of the closed loop systems in spite of parameter uncertainties, time delay, and controller fragility.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1970-1972
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• 2001

This paper is concerned with the $H_{\infty}$ controller design of linear systems subject to time-delay in the state and saturating controls. The controller is derived from the matrix inequalities whish are obtained by minimizing the $L_{2}$ gain from the disturbance to the measured output, and this can be done by LMI control toolbox. An example is presented to show the usefulness of our result.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.5
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• pp.64-72
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• 2004

An extension of interaction matrix formulation to the problem of system and disturbance identification for a plant that is corrupted by both process and output disturbances is presented. The teaming control develops controllers that learn to improve their performance at executing a given task, based on experience performing this task. The simplest forms of loaming control are based on the same concept as integral control, but operating in the domain of the repetitions of the task. This paper studies the use of such controllers in a decentralized system, such as a robot moving on the vertical plane with the controller for each link acting independently. The basic result of the paper is to show that stability and iterative precision of the learning controllers for all subsystems when the coupling between subsystems is turned off, assures stability of the decentralized teaming in the coupled system, provided that the sample time in the digital teaming controller is sufficiently short. The methods of teaming system are shown up for the iterative precision of each link.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.401-408
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• 2006

An optimum design method for hybrid control systems is proposed in this study. By considering both active and passive control systems as a combined or a hybrid system, the optimization of the hybrid system can be achieved simultaneously. In the proposed approach, we consider design parameters of active control devices and the elements of the feedback gain matrix as design variables for the active control system. Required quantity of the added dampers are also treated as design variables for the passive control system. In the proposed method, the cost of both active and passive control devices, the required control efforts and dynamic responses of a target structure are selected as objective functions to be minimized. To effectively address the multi-objective optimization problem, we adopt a preference-based optimization model and apply a genetic algorithm as a numerical searching technique. As an example to verify the validity of the proposed optimization technique, a wind-excited 20-storey building with hybrid control systems is used and the results are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.87.1-87
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• 2001

For a plant subject to several kinds of disturbances in the plant input side, we consider a problem of designing a controller based on the disturbance cancellation. The conventional loop transfer recovery (LTR) technique can not be used since the extended system consisting of the plant and the disturbance model is not necessarily stabilizable. We propose a new LTR technique that can be applied for our problem. As a target of the LTR, we choose a state feedback controller using a disturbance estimator. We find an LTR procedure based on the Riccati equation formalism where the stochastic model contains the filter gain matrix of the disturbance estimator in the target. The procedure recovers the target feedback ...

• Journal of the Korean Magnetics Society
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• v.5 no.5
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• pp.421-426
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• 1995

The magnetic properties of the hot-pressed magnets made from the Fe-Nd-B alloys, mechanically ground and subsequently blended with binary additives such as Al-Cu and Ag-Zn before hot pressing, were investigated. The coercivities of the magnets increased as the concentration of Al-Cu increased up to 1 wt.% or up to 3 wt.% in the case of Ag-Zn. At higher concentrations the coercivities decreased markedly. The maximum gain in coercivity by the addition was about 20 %. typical values of $_{i}H_{c}$ and $B_{r}$ of a hotpressed magnet containing 1 wt.% Al-Cu were 18 kOe and 7 kG, respectively. It was found that Cu, Ag, and Zn, which diffused into the magnet during hot pressing, were mostly concentrated on the Nd-rich grain boundary phase whereas Al was present not only in the grain boundary region but also in the matrix grains.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2407-2424
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• 2022

Recently, Transformer has made great progress in video retrieval tasks due to its high representation capability. For the structure of a Transformer, the cascaded self-attention modules are capable of capturing long-distance feature dependencies. However, the local feature details are likely to have deteriorated. In addition, increasing the depth of the structure is likely to produce learning bias in the learned features. In this paper, an improved Transformer structure named TransDCS (Transformer with Dynamic Convolution and Shortcut) is proposed. A Multi-head Conv-Self-Attention module is introduced to model the local dependencies and improve the efficiency of local features extraction. Meanwhile, the augmented shortcuts module based on a dual identity matrix is applied to enhance the conduction of input features, and mitigate the learning bias. The proposed model is tested on MSRVTT, LSMDC and Activity-Net benchmarks, and it surpasses all previous solutions for the video-text retrieval task. For example, on the LSMDC benchmark, a gain of about 2.3% MdR and 6.1% MnR is obtained over recently proposed multimodal-based methods.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.73-78
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• 2022

Based on experimental measurements conducted on many different practical wireless communication systems, ambient noise has been shown to be decidedly non-Gaussian owing to impulsive phenomena. However, most multiuser detection techniques proposed thus far have considered Gaussian noise only. They may therefore suffer from a considerable performance loss in the presence of impulsive ambient noise. In this paper, we consider a large-scale multiuser multiple-input multiple-output system in the presence of non-Gaussian noise and propose a genetic algorithm (GA) based detector for large-dimensional multiuser signal detection. The proposed algorithm is more robust than linear multi-user detectors for non-Gaussian noise because it uses a multi-directional search to manipulate and maintain a population of potential solutions. Meanwhile, the proposed GA-based algorithm has a comparable complexity because it does not require any complicated computations (e.g., a matrix inverse or derivation). The simulation results show that the GA offers a performance gain over the linear minimum mean square error algorithm for both non-Gaussian and Gaussian noise.

• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1068-1074
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• 2011

In this paper, the proposed scheme is STBC(space-time block codes) system combined with convolution code which is the most popular channel coding to ensure the reliability of data transmission for a high data rate wireless communication. The STBC is one of MIMO(multi-input multi-output) techniques. In addition, this scheme uses a modified viterbi algorithm in order to get a high system gain when data is transmitted. Because we combine STBC and convolution code, the proposed scheme has a little high quantity of computation but it can get a maximal diversity gain of STBC and a high coding gain of convolution code at the same time. Unlike existing viterbi docoding algorithm using Hamming distance in order to calculate branch matrix, the modified viterbi algorithm uses Euclidean distance value between received symbol and reference symbol. Simulation results show that the modified viterbi algorithm improved gain 7.5 dB on STBC 2Tx-2Rx at $BER=10^{-2}$. Therefore the proposed scheme using STBC combined with convolution code can improve the transmission reliability and transmission efficiency.