• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.113-118
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• 1999

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important n the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.177-182
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• 1994

In this paper, an output feedback adaptive variable structure control scheme is presented for stabilization of large scale power systems. An additional input signal which is called a power system stabilizer(PSS) is needed to improve the stability of a power system and to maintain the synchronization of generators. The proposed PSS scheme does not require a priori knowledge of uncertainty bounds. It is guaranteed that the closed-loop system is globally uniformly ultimately bounded by the Lyapunov stability theory. Simulation results for a multimachine power system are given to show the feasibility of the proposed scheme and the superiority of the proposed PSS in comparison with the conventional lead-lag PSS of PID-type.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.129-133
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• 2008

In this paper, modified power control algorithms are proposed for a satellite mobile communications system with ATC (ancillary terrestrial component). In order to increase system capacity and reduce the transmitting power of the user's equipment, we propose the modified power control scheme consisting of the modified closed-loop and open-loop power control. The modified CLPC (closed-loop power control) algorithm, combining the delay compensation algorithms and pilot diversity, is mainly applied to the ATC link in urban areas because it is more suitable to the short RTD (round-trip delay). In the case of rural areas where ATCs are not deployed or a signal is not received from ATCs, combining monitoring transmitting power equipment and OLPC (open-loop power control) algorithms using an efficient pilot diversity is mainly applied to the link between the user's equipment and the satellite. Two power control algorithms are applied equally to the boundary areas where two kinds of signals are received in order to ensure coverage continuity. The simulation results show that the modified power control scheme has good performance compared to conventional power control schemes in a GEO (geostationary earth orbit) satellite system with ATC.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.646-652
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• 2013

EU's Galileo project is a market-based GNSS (Global Navigation Satellite System) that is under development. It is expected that Galileo will provide the positioning services based on new technologies in 2020s. Because Galileo E1 signal for OS (Open Service) shares the same center frequency with GPS L1 C/A signal, CBOC (Composite Binary Offset Carrier) modulation scheme is used in the E1 signal to guarantee interoperability between two systems. With E1 signal consisting of a data channel and a pilot channel at the same frequency band, there exist several options in designing signal acquisition for Assisted-Galileo receivers. Furthermore, compared to SNR worksheet of Assisted-GPS, some factors should be examined in Assisted-Galileo due to different correlation profile and code length of E1 signal. This paper presents SNR worksheets of Galileo E1 signals in E1-B and E1-C channel. Three implementation losses that are quite different from GPS are mainly analyzed in establishing SNR worksheets. In the worksheet, hybrid long integration of 1.5s is considered to acquire weak signal less than -150dBm. Simulation results show that the final SNR of E1-B signal with -150dBm is 19.4dB and that of E1-C signal is 25.2dB. Comparison of relative computation shows that E1-B channel is more profitable to acquire the strongest signal in weak signal environment. With information from the first satellite signal acquisition, fast acquisition of the weak signal around -155dBm can be performed with E1-C signal in the subsequent satellites.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.286-286
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.154-161
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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• pp.1029-1034
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• 2010

For All Digital QPSK receivers, a phase recovery scheme is required to fix the arbitrarily rotated I/Q quadrature signals due to the transmission path and clock mismatch between the transmitter and the receiver. The conventional Costas phase recovery loop scheme requires a separate AGC(Automatic Gain Control) to obtain the performance independent of input signal power. This paper proposes a simple scheme which separates the phase and amplitude of the input signal via CORDIC algorithm and performs the phase recovery and amplitude compensation simultaneously. The proposed scheme can considerably reduce the logic resources in hardware implementation, has been verified by C++ and Model Sim simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4B
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• pp.306-315
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• 2003

On the optical network, it is important to build restoration scheme capable to network survivability in preparation of potential failure on communication route. This analyze the existing schemes on restoration of failure on the optical network, and propose deferred commit scheme to improve resource utilization signal management efficiency. Also, the transfer flow of messages needed for transferring restoration signal are presented in a concrete way and delay time required by shared mesh restoration scheme is explained in a substantial way. Simulation-based comparative analysis of various scheme is performed.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.720-725
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• 2010

In AGPS method, user position can be obtained even in the shadow region by improving signal sensitivity. A hybrid long integration scheme employing both coherent and non-coherent integration method is commonly used in AGPS receivers. Because coherent loss increases as residual frequency become large, residual frequency should be minimized to maximize coherent integration gain. This paper presents performance analysis of residual frequency estimator using FFT in fine-time assistance AGPS method. Considering the hardware complexity and the estimation accuracy, optimal length of FFT is proposed for GPS L1 C/A signal. Signal sensitivity for estimating the residual frequency is also analysed. By field experimental results, it is found that the residual frequency can be successfully estimated using 1 second snap-shot data when GPS signal strength is larger than -150 dBm and its RMS error is 3Hz.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.1
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• pp.18-30
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• 2016

In this paper, we propose a new technique to the design and real-time control of an adaptive controller for robotic manipulator based on digital signal processors. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot manipulator with eight joints. joint space and cartesian space.