• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2268-2271
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• 1998

This paper proposes a method which can resolve the problem of existing fuzzy Pl controller using optimal scaling gains obtained by genetic algorithm. The new method adapt a fuzzy logic controller as a high level controller to perform scaling gain algorithm between two pre-determined sets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.303-310
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• 2014

We show improved throughput scaling laws for an ultra-wide band (UWB) ad hoc network, in which n wireless nodes are randomly located. First, we consider the case where a modified hierarchical cooperation (HC) strategy is used. Then, in a dense network of unit area, our result indicates that the derived throughput scaling depends on the path-loss exponent ${\alpha}$ for certain operating regimes due to the power-limited characteristics. It also turns out that the HC protocol is dominant for 2 < ${\alpha}$ < 3 while using the nearest multihop (MH) routing leads to a higher throughput for ${\alpha}{\geq}3$. Second, the impact and benefits of infrastructure support are analyzed, where m base stations (BSs) are regularly placed in UWB networks. In this case, the derived throughput scaling depends on ${\alpha}$ due to the power-limited characteristics for all operating regimes. Furthermore, it is shown that the total throughput scales linearly with parameter m as m is larger than a certain level. Hence, the use of either HC or infrastructure is helpful in improving the throughput of UWB networks in some conditions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.1
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• pp.27-33
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• 2009

Human postural responses appeared to have stereotyped modality, such as ankle mode, knee mode and hip mode in response to various perturbations. We examined whether human postural control gain of full-state feedback could be decoupled along with the eigenvector. To verify the model, postural responses subjected to fast backward perturbation were used. Upright posture was modeled as 3-segment inverted pendulum incorporated with feedback control, and joint torques were calculated using inverse dynamics. Postural modalities such as ankle, knee and hip mode were obtained from eigenvectors of biomechanical model. As oppose to the full-state feedback control, independent eigenvector control assumes that modal control input is determined by the linear combination of corresponding modality. We used optimization method to obtain and compare the feedback gains for both independent eigenvector control and full-state feedback control. As a result, we found that simulation result of eigenvector feedback was not competitive in comparison with that of full-state feedback control. This implies that the CNS would make use of full-state body information to generate compensative joint torques.