• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.719-724
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• 2012

A traffic detection system is a device that collects traffic information around an intersection. Most existing traffic detection systems provide very limited traffic information for signal control due to the restriction of vehicle detection area. A signal control scheme determines the transition among signal phases and the time that a phase lasts for. However, the existing signal control scheme do not resolve the traffic congestion effectively since they use restricted traffic information. In this paper, a new traffic detection system with a zone division signal control scheme is proposed to provide correct and detail traffic information and decrease the vehicle's waiting time at the intersection. The traffic detection system obtains traffic information in a way of vehicle-to-roadside communication between vehicles and sensor network. A new signal control scheme is built to exploit the sufficient traffic information provided by the proposed traffic detection system efficiently. Simulation results show that the proposed signal control scheme has 121 % and 56 % lower waiting time and delay time of vehicles at an intersection than other fuzzy signal control scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.483-489
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• 2016

This paper proposes a repeat-back jamming signal detection scheme that utilizes a combined pseudo random noise signal that is effective for processing a global positioning system (GPS) repeat-back jamming signal with the early minus late phase scheme to alleviate any existing multipath signal detection. The proposed scheme uses the combined pseudo random noise signal to treat repeat-back jamming signals like similar multipath signals and can effectively detect a repeat-back jamming signal by applying the early minus late phase scheme to a combined pseudo random noise signal. Through a Monte-Carlo simulation, the detection probability of the proposed scheme is better than the one of the conventional scheme under low jamming to signal power ratio.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.665-670
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• 2016

This paper proposes a repeat-back jamming signal detection scheme using a correlation ratio test metric of a combined pseudo-random noise signal for global navigation satellite systems. The correlation ratio test metric allows for the monitoring of possible distortions in the signal correlation. The proposed scheme is a modified version of the correlation ratio test metric to detect a repeat-back jamming signal in a multipath environment. Through a Monte-Carlo simulation, it is confirmed that the proposed scheme detects almost the whole case, which is received a repeat-back jamming signal under the 6 dB jamming to signal power ratio.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.1
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• pp.7-17
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• 1997

During the past decade, there were many well-established theories for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.454-459
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• 1997

The good features of a switched reluctance motor(SRM) are appreciated by the appliance manufactures. And it is spread into a commercial and industries market. The few disadvantage of the motor is higher torque ripple and noise. This paper proposes an instantaneous torque control scheme to control a speed precisely. It adapts phase-locked loop (PLL) technique to control speed precisely. In this control scheme, the phase detector signal of the PLL regulates the switching dwell angle flexibly and the loop filter's signal controls adaptively the instantaneous switching voltage. Experimental results show that drive performance is good with low torque ripple.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.157-160
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• 2002

When the teleoperation system has a signal transmission time delay between slave system and control system, the position tracking performance of the slave system and system stability are likely to be deteriorated. This paper proposes a force reflecting position control scheme for teleoperation system with signal transmission time delay. The proposed scheme not only satisfy the system internal stability but also improves the position tracking performance with disturbance rejection capability. The simulation results show that the proposed control method provides excellent performances.

• Journal of Power Electronics
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• v.10 no.1
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• pp.1-8
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• 2010

A new scheme for sliding-mode control (SMC) of DC-DC converters with a constant switching frequency is proposed. The scheme is based on the averaging model and the output signal of the controller is $d^+$ or $d^-$ instead of the on or off signal of a direct sliding-mode (SM) controller or the continuous signal d = $u_{eq}$ of an indirect SM controller. Two approaches using the new scheme are also proposed and the design procedures for a buck converter are given in detail. The first approach called constant $d^+$ and $d^-$ SMC is simple, cost effective and dynamically fast. In order to improve the dynamic characteristics of the reaching phase and to alleviate chattering, the second approach called reaching law SMC is also presented. Analyses and simulation results demonstrate the feasibility of the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.977-983
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• 2014

A repeat-back jamming signal is an intentionally re-broadcasted GNSS (Global Navigation Satellite System) interference. In this paper, a novel repeat-back jamming detection scheme is proposed. The proposed scheme uses a combined pseudo random noise signal (C-PRN) and is available for a generic GNSS receiver with a single antenna. The C-PRN signal is made by combining several received pseudo random noise signals that had been transmitted from the visible GNSS satellites. Through a Monte-Carlo simulation, the detection probability of a repeat-back jamming signal detected with the proposed scheme is presented.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.2
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• pp.38-47
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• 2001

In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.344-350
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• 2006

The software GPS receivers based on the SDR technology provide the ability to easily adapt the other signal processing algorithms without changing or modifying the hardware of the GPS receiver. However, it is difficult to implement the software GPS receivers using a commercial processor because of the heavy computational burden for processing the GPS signals in real-time. This paper proposes an efficient GPS signal processing scheme to reduce the computational burden for processing the GPS signals in the software GPS receiver, which uses a fundamental notion compressing the replica signals and the encoded look-up table method to generate correlation values between GPS signals and replica signals. In this paper, it is explained that the computational burden of the proposed scheme is much smaller than that of the typical GPS signal processing scheme. Finally, the processing time of the proposed scheme is compared with that of the typical scheme, and the improvement in the aspect of the computational burden is also shown.