• Journal of Sensor Science and Technology
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• v.29 no.3
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• pp.149-155
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• 2020

In this study, we employed Manchester code for illumination control and flicker prevention of the light-emitting diode (LED) used in a visible light communication (VLC) system. In the VLC transmitter, the duty factor of the Manchester code was utilized for illumination control; in the VLC receiver, the spike signal from an RC-high pass filter was utilized to recover the transmitted signal whilst suppressing the 120-Hz noise arising from adjacent lighting lamps. Instead of the clock being transmitted in a separate channel, a syncmark signal was transmitted in front of each data byte and used as the reference time for transforming the Manchester code to non-return-to-zero (NRZ) data in the receiver. In experiments, the LED illumination was controlled in the range of approximately 12-84% of the constant wave (CW) light via changing of the duty factor from 10% to 90%. This scheme is useful for constructing indoor wireless sensor networks using LED light that is flicker-free and presents capability for illumination control.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.62-67
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• 1997

This paper reprdsents a new scheme of neural network control system analysis the robustues of robot manipulator using digital signal processors. Digtal signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In additions, DSPs are a s fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Durng past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. The proposed neuro network control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.

• 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.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.35-38
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• 2000

Since the telemanipulator consisting of high reduction ratio gear joints has a slow dynamics comparing with the master manipulator, its control signal is likely to be saturated resulting in poor tracking performance and deteriorated stability. This paper proposes a bilateral control scheme of a telemanipulator having high reduction ratio, which can compensate the control input saturation. The experimental results show that the proposed control scheme has excellent performances.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.478-482
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C50) for robotic manipulators to achieve trajectorytracking angles. Digital signal processors are used in implementing real time adaptive control algorithms to provide motion for robotic manipulators. In the proposed scheme, adapation laws are derived from the improved second stability analysis based on the indirect adaptive control theory.l The proposed control scheme is simple in structure, fast in computation, an suitable for implementation of real-time control. Moreover, this scheme does not requre an accurate dynamic modeling, nor values of manipulator paramenters and payload Performance of the adaptive controller is illustrated by exeperimental results for a SCARA robot.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.1
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• pp.54-60
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• 2020

A digital current control scheme using virtual d-q transformation for a boost single-phase power factor correction (PFC) converter is proposed. The use of virtual d-q transformation in single-phase power converters is known to improve current control performance. However, the conventional virtual d-q transformation-based digital current control scheme cannot be directly applied to the boost single-phase PFC converter because the current and average voltage waveforms of the inductor used in the converter are not sinusoidal. To cope with this problem, this study proposes a virtual sinusoidal signal generation method that converts the current and average voltage waveform of the inductor into a sinusoidal waveform synchronized with the grid. Simulation and experimental results are provided to show that the virtual d-q transformation-based digital current control is successfully applied to the boost single-phase PFC converter with the aid of the proposed virtual sinusoidal signal generation method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.136-144
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• 2014

The existing conventional motion controller does not perform well in the presence of nonlinear properties, uncertain factors, and servo lag phenomena of industrial actuators. Hence, a feasible and effective fuzzy self-tuning proportional integral derivative (PID) and feed-forward control scheme is introduced to overcome these problems. In this design, a fuzzy tuner is used to tune the PID parameters resulting in the rejection of the disturbance, which achieves better performance. Then, both velocity and acceleration feed-forward units are added to considerably reduce the tracking error due to servo lag. To verify the capability and effectiveness of the proposed control scheme, the hardware configuration includes digital signal processing (DSP) which plays the main role, dual-port RAM (DPRAM) to guarantee rapid and reliable communication with the host, field-programmable gate array (FPGA) to handle the task of the address decoder and receive the feed-back encoder signal, and several peripheral logic circuits. The results from the experiments show that the proposed motion controller has a smooth profile, with high tracking precision and real-time performance, which are applicable in various manufacturing fields.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1982-1985
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• 2003

Future cellular networks will mainly be driven by, high quality channels, high band with utilization, low power consumption and efficient network management. For a given channel allocation, the capacity and quality of communication of cellular radio systems using CDMA(Code Division Multiple Access) can be increased by using a transmitter power control scheme to combat the near-far problem. Centralized power control schemes or distributed ones to maximize the minimum signal-to-interference in each user of CDMA wireless network have been investigated. This paper has proposed a distributed power control algorithm, which employs an adaptive search scheme, in order to solve quickly the linear systems of equations for power update in CDMA cellular radio systems. The simulation results show that the proposed scheme has faster convergence rate than the typical bang-bang type of distributed power control algorithm, which has been much used as a reference algorithm in IS-95A and W-CDMA communication network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4268-4289
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• 2020

Advanced traffic signal timing method plays very important role in reducing road congestion and air pollution. Reinforcement learning is considered as superior approach to build traffic light timing scheme by many recent studies. It fulfills real adaptive control by the means of taking real-time traffic information as state, and adjusting traffic light scheme as action. However, existing works behave inefficient in complex intersections and they are lack of feasibility because most of them adopt traffic light scheme whose phase sequence is flexible. To address these issues, a novel adaptive traffic signal timing scheme is proposed. It's based on actor-critic reinforcement learning algorithm, and advanced techniques proximal policy optimization and generalized advantage estimation are integrated. In particular, a new kind of reward function and a simplified form of state representation are carefully defined, and they facilitate to improve the learning efficiency and reduce the computational complexity, respectively. Meanwhile, a fixed phase sequence signal scheme is derived, and constraint on the variations of successive phase durations is introduced, which enhances its feasibility and robustness in field applications. The proposed scheme is verified through field-data-based experiments in both medium and high traffic density scenarios. Simulation results exhibit remarkable improvement in traffic performance as well as the learning efficiency comparing with the existing reinforcement learning-based methods such as 3DQN and DDQN.

• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.49-56
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• 2010

Severe energy constraints and the low power consumption require the significance of the energy efficient error control mechanisms in wireless sensor network (WSN). In this paper, an automatic repeat request (ARQ) methodology for the analysis of error control schemes in WSN is presented such that the effects of packet length, the modulation scheme and the interference effect of the wireless channel are investigated. Moreover, an analyis of ARQ error control is provided by considering two major architectures for wireless sensor network, i.e., Mica2 and MicaZ sensor nodes. And the throughput performance of WSN with asynchronous FSK signal and DSSS-OQPSK signal with selective repeat ARQ scheme are analyzed in multiple interference environment, and the probability of receiving a correct bit and packet from target node to sink node is evaluated as a function of the channel parameter, the number of wireless sensor node, and the spreading factor.