• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1A
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• pp.34-43
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• 2007

In the IEEE 802.15.3 Medium Access Control (MAC) protocol, Simultaneously Operating Piconets (SOPs) are linked by the parent/child (P/C) or parent/neighbor (P/N) configuration, which work on a Time Division Multiple Access (TDMA) basis. This provides interference mitigation but the overall throughput is limited because the SOPs share the channel time exclusively. The protocol is not efficient for SOPs if we focus on the combination of interference mitigation and high throughput maintenance. In this paper Public Channel Time Allocation (Public CTA) is proposed, which is able to greatly reduce the inter-piconet interference (IPI) and achieve greater throughput without much loss of link success probability (LSP) in the SOPs. The simulation results based on the SOPs of Direct Sequence Ultra Wideband (DS-UWB) system demonstrate that the proposed scheme effectively supports the coexistence of SOPs, and it can not only significantly improve the overall throughput of SOPs but also maintain high LSP.

• The KIPS Transactions:PartC
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• v.17C no.6
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• pp.459-464
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• 2010

Due to the application-specific nature of wireless sensor networks, the sensitivity to such a requirement as data reporting latency may vary depending on the type of applications, thus requiring application-specific algorithm and protocol design paradigms which help us to maximize energy conservation and thus the network lifetime. In this paper, we implement and evaluate a novel delay-adaptive sensor scheduling scheme for energy-saving data gathering which is based on a two phase clustering (TPC), in wireless sensor networks. The TPC is implemented on sensor Mote hardwares. With the help of TPC implemented, sensors selectively use direct links for control and forwarding time critical sensed data and relay links for data forwarding based on the user delay constraints given. Implementation study shows that TPC helps the sensors to increase a significant amount of energy while collecting sensed data from sensors in a real environment.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.47-59
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• 2009

Due to the application-specific nature of wireless sensor networks, the sensitivity to such a requirement as data reporting latency may vary depending on the type of applications, thus requiring application-specific algorithm and protocol design paradigms which help us to maximize energy conservation and thus the network lifetime. In this paper, we propose a novel delay-adaptive sensor scheduling scheme for energy-saving data gathering which is based on a two phase clustering (TPC). The ultimate goal is to extend the network lifetime by providing sensors with high adaptability to the application-dependent and time-varying delay requirements. The TPC requests sensors to construct two types of links: direct and relay links. The direct links are used for control and forwarding time critical sensed data. On the other hand, the relay links are used only for data forwarding based on the user delay constraints, thus allowing the sensors to opportunistically use the most energy-saving links and forming a multi-hop path. Simulation results demonstrate that cluster-based delay-adaptive data gathering strategy (CD-DGS) saves a significant amount of energy for dense sensor networks by adapting to the user delay constraints.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.111-118
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.4
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• pp.65-73
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• 2002

It has been recognized that the damage control must become a more explicit design consideration. In an effort to develop design methods based on performance it is clear that the evaluation of the nonlinear response is required. The methods available to the design engineer today are nonlinear time history analyses, monotonic static nonlinear analyses, or equivalent static analyses with simulated nonlinear influences. Some building codes propose the capacity spectrum method based on the nonlinear static analysis(pushover analysis) to determine the earthquake-induced demand given by the structure pushover curve. These procedures are conceptually simple but iterative and time consuming with some errors. This paper presents a nonlinear direct spectrum method(NDSM) to evaluate seismic performance of structures, without iterative computations, given by the structural initial elastic period and yield strength from the pushover analysis, especially for MDF(multi degree of freedom) systems. The purpose of this paper is to investigate the accuracy and confidence of this method from a point of view of various earthquakes and unloading stiffness degradation parameters. The conclusions of this study are as follows; 1) NDSM is considered as practical method because the peak deformations of nonlinear system of MDF by NDSM are almost equal to the results of nonlinear time history analysis(NTHA) for various ground motions. 2) When the results of NDSM are compared with those of NTHA. mean of errors is the smallest in case of post-yielding stiffness factor 0.1, static force by MAD(modal adaptive distribution) and unloading stiffness degradation factor 0.2~0.3.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1025-1031
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• 2011

Take-out robots used for handling of the plastic parts manufactured with the injection mold are usually the gantry type that consists of long and thin links, The performance of the take-out robot is determined by the speed of the motion and the positioning accuracy to grab the part out of the mold, As the speed of the robot increases the flexure in the links of the take-out robot becomes more significant and it results in more residual vibration, The residual vibration deteriorates the positioning accuracy and compels the operator to slow down the motion of the robot. The typical method to reduce the vibration in the robot requires stiffening the links and/or slowing down the robot, Vibration control could achieve the desired performance without increasing the manufacturing cost or the operation cost that would be incurred otherwise, Considering the point-to-point nature of the task to be performed by the take-out robot the time-delay command (or input) shaping filter approach would be the most effective control method to be adopted among a few available control schemes. In this paper a direct adaptive command shaping filter (ACSF) algorithm has been modified and applied to design the optimal command shaping filters for various configuration of the take-out robot. Optimal filters designed by ACSF algorithm have been implemented on a take-out robot and the effectiveness of the designed filters in terms of vibration suppression has been verified for multiple positions of the robot.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.5
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• pp.46-55
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• 2000

This paper presents a direct adaptive control of robot system using chaotic neural networks and PD controller. The chaotic neural networks have robust nonlinear dynamic characteristics because of the sufficient nonlinearity in neuron itself, and the additional self-feedback and inter-connecting weights between neurons in same layer. Since the structure and the learning method are not appropriate for applying in control system, this neural networks have not been applied. In this paper, a modified chaotic neural networks is presented for dynamic control system. To evaluate the performance of the proposed neural networks, these networks are applied to the trajectory control of the three-axis PUMA robot. The structure of controller consists of PD controller and chaotic neural networks in parallel for conforming the stability in initial learning phase. Therefore, the chaotic neural network controller acts as a compensating controller of PD controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.2
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• pp.114-123
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• 2005

A nonlinear speed control of a PMSM using a sequential parameter auto-tuning algorithm for servo equipments is presented. The nonlinear control scheme gives an undesirable output performance under the mismatch of the system parameters and load conditions. Recently, to improve the performance, an adaptive linearization scheme, a sliding mode control and an observer-based technique have been reported. Although a good performance can be obtained, the performance is not satisfactory any more under specific conditions such as a large inertia variation, a fast speed transient or an increased sampling time. The simultaneous estimation of principal parameters giving a direct influence on speed dynamics is generally not simple. To overcome this problem, a a sequential parameter auto-tuning algorithm at start-up is proposed, where dominant parameters are estimated in a prescribed regular sequence based on the method that one parameter is estimated during each interval. The proposed scheme is implemented on a PMSM using DSP TMS320C31 and the effectiveness is verified through simulations and experiments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2285-2291
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• 2011

In this paper, H.264 high profile intra frame encoder, which integrates intra prediction, context-based adaptive variable length coding(CAVLC), and DDR2 memory control module, is proposed. The designed encoder can be operated in 440 cycle for one-macroblock. In order to verify the encoder function, we developed the reference C from JM 13.2 and verified the developed hardware using test vector generated by reference C. The designed encoder is verified in the FPGA (field programmable gate array) with operating frequency of 200 MHz for DMA (direct memory access), operating frequency of 50 MHz of Encoder module, and 25 MHz for VIM(video input module). The number of LUT is 43099, which is about 20 % of Virtex 5 XC5VLX330.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.3
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• pp.174-181
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• 2018

This study introduces a systematic approach to selecting the internal parameters applied to the equivalent electrical-circuit model (EECM) of a lithium titanium oxide ($Li_4Ti_5O_{12}$; LTO) rechargeable cell. Based on the dynamic characteristic of the cell, a simplified EECM consisting of an open-circuit voltage (OCV), an ohmic resistance, and an RC ladder is fabricated. To select the internal parameters of a simplified EECM, experiments on discharge capacity, OCV, and discharge/charge resistances are performed using hybrid pulse power characterization and direct current internal resistance (DCIR) measurements over the full state-of-charge (SOC) range. The experimental results of the LTO rechargeable cell highlight the importance of correct selection of internal parameters that can reduce EECM errors. This study clearly provides experimental procedures, internal parameters results, and EECM guidelines for adaptive control-based SOC estimation for LTO rechargeable cells.