• The Journal of Information Systems
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• v.18 no.2
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• pp.35-59
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• 2009

The study of Information Systems(IS) is a relatively new discipline area, thus an analysis of the latest research literature could be useful to identify what the researchers are doing and what can be done to improve our discipline. With that purpose in mind, this study analyzes the total 208 articles published in "The Journal of Information Systems~ between 2001 and 2008. The classification system that comprises three key characteristics of diversity (research topic, research method, and reference discipline) was developed based on a review of prior literature. The results of this study were also compared with Kim et al.(2005)'s and Vessey et al.(2002)'s results to identify issues in current Information Systems research and 10 suggest some recommendations for future In formation Systems research. The findings identify popular research topic:s, the dominant research method, and reference discipline. The popular research topics consists of organizational concepts, problem domain-specific concepts, and systems/software management concepts. Field study was characterized as the dominant research method in the papers included in the study. Information Systems itself represents the major theoretical reference of the studies. However, many papers in this study relied on a number of reference disciplines., none of which was dominant, or they did not rely on a specific reference discipline. Finally, this study suggests more research on the disciplinary issues, more training on the research method, more accurate and specific reference discipline, and controlled diversity.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.166-173
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• 1999

Reference models are used in many control algorithms for improvement of transient response characteristics. They provide desired trajectories that the plant should follow Most control systems have bounded control inputs to avoid saturation of the plant. If we design the reference models that do not account for limits of the control inputs, control performance of the system may be deteriorated. In this paper a new approach of avoiding saturation by varying the reference model for TDC(time delay control) based systems subject to step changes in the reference input. In this scheme, the variable reference model is determined based on the information on control inputs and the size of the step changes in the reference inputs. This scheme was verified by application to the BLDC motor position control system in simulations and experiments. The responses of the TDC with the variable reference model showed better tracking performance than that with the fixed reference model.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.241-247
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• 2000

The reference model of an MRC (model reference control) provides the desired trajectory a plant should follow and thus the design of a reference model has a significant effect on control performance. In most control systems control input to a plant has some bounds and it is preferable to make use of as large control inputs as possible within the range of no saturation. In this paper a new approach of selecting the reference model is proposed for bounded control inputs. Design variables of the reference model are determined in such a way that maximizes the performance index within the range of no saturation. Moreover this variable reference model is regularly updated during control. This scheme is verified by application to the servo motor position control system in various simulations. The responses of the MRC with a variable reference model show better tracking performance than that with a fixed reference mode. Moreover by adjusting the update interval of the reference model the control performance can be further improved.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.32-42
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• 2001

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured stated with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, and indirect Model Reference Adaptive Fuzzy control(MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain for slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop systems. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.721-723
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• 1987

An Adaptation algorithm is presented and a convergence criterion is derived for parallel model reference adaptive bilinear systems. The output error converges asymptotically to zero, and the parameter estimates are bounded for stable reference models. The convergence criterion depends only upon the input sequence and a priori estimates of the maximum parameter values.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.79-87
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• 1999

For its simplicity and cost effectiveness in implementation, the Inverted DGPS is well suited for some specific applications like automatic vehicle location systems, where the monitoring station needs accurate position of the vehicles in the street. In the Inverted DGPS, the user sends its GPS position and associated satellite informations to the reference station, and the corrections are made at the reference station to get differentially corrected user position. A fundamental requirement in IDGPS is that the user and the reference station must use the same satellites when the corrections are made. But in practice, it is not often satisfied. Inverted DGPS is also suffered from performance degradation as the baseline become large like DGPS. IDGPS system using multi-reference station can resolve this problem. In this paper a simple multi-reference IDGPS algorithm is proposed and some experiments and analysis are peformed. Experiment results show that IDGPS can achieve the positioning performance as accurate as the DGPS can provide.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.6
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• pp.466-472
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• 2003

This paper describes a tracking control for the mobile robot based on fuzzy systems. Since the mobile robot has the nonholonomic constraints, these constraints should be considered to design a tracking controller for the mobile robot. One of the well-known tracking controllers for the mobile robot is the back-stepping controller. The conventional back-stepping controller includes the dynamics and kinematics of the mobile robot. The conventional back-stepping controller is affected by the derived velocity reference by a kinematic controller. To improve the performance of the conventional back-stepping controller, this paper uses the fuzzy systems known as the nonlinear controller. The new velocity reference for the back-stepping controller is derived through the fuzzy inference. Fuzzy rules are selected for gains of the kinematic controller. The produced velocity reference has properly considered the varying reference trajectories. Simulation results show that the proposed controller is more robust than the conventional back-stepping controller.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.630-642
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• 2007

In this paper, we propose a direct model reference adaptive fuzzy control (MRAFC) for MIMO nonlinear systems whose structure is represented by the Takagi-Sugeno fuzzy model. The adaptive law of the MRAFC estimates the approximation error of the fuzzy logic system so that it provides asymptotic tracking of the reference signal for the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop system. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal. To verify the validity and effectiveness of the MRAFC scheme, the suggested analysis and design techniques are applied to the tracking control of robot manipulator and simulation studies are carried out. In the control design, the MRAFC is combined with feedforward PD control to make the actual joint trajectories of the robot manipulator with system uncertainties track the desired reference joint position trajectories asymptotically stably.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.540-547
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• 2009

In this paper, we propose a transceiver structure that can effectively improve BER(Bit Error Rate) performance for TR-UWB (Transmitted Reference Ultra Wide Band) systems based on impulse radio. Unlike coherent UWB systems that are too complex for practical implementation while having good BER performances, the complexity of the TR-UWB systems is quite low since they transmit data with the corresponding reference signals and demodulate the data through correlation using these received signals. However, the BER performance in the conventional TR-UWB systems is affected by SNR (Signal-to-Noise Ratio) of the reference templates used in the correlator. To this end, we propose a receiver structure that can effectively improve the BER performance by increasing the SNR of reference templates. Simulation results reveal that the proposed scheme achieves significant BER improvement as compared to the conventional TR-UWB systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.130-135
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• 2007

In this paper, a direct model reference adaptive fuzzy control (MRAFC) scheme is developed for the plant model whose structure is represented by the MIMO Takagi-Sugeno fuzzy model. The MRAFC scheme is proposed to provide asymptotic tracking of a reference signal lot the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee that all signals in the closed-loop system are bounded. In addition, the plant state tracks the state of the reference model asymptotically with time tot any bounded reference input signal.