• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.497-497
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• 2000

This paper is concerned with the design of LMI based H$_{\infty}$ controller for a line of sight(LOS) stabilization system. This system which is even linearized to analyse nonlinear characteristic has also a lot of uncertainties. In addition, the angular velocity disturbance from the vehicle's driving deteriorates the stabilized LOS, main purpose of this system. In case of fast driving, particularly, all components which are ignored and skipped to make mathematical modelling act as the uncertainties against this system. The robustness against these uncertainties has been also continuously demanded including the well tracking performance for the target. Therefore, this paper employed H$_{\infty}$ control theory to satisfy these problems and LMI method to make suitable controller with few constraints for this system. Although this system matrix doesn't have full rank, this method make it possible to design H$_{\infty}$ controller and deal with R and S matrices for reducing its order. Consequently, this paper shows that the re-analyses on the real disturbances are achieved and the proposed robust controller for them has better disturbance attenuation and tracking performance. This paper contributes the applicability of reduced order H$_{\infty}$ controller to real system by handling LMI..

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.45-46
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• 2006

In this paper, a dual stage servo mechanism has been developed for image tracking system to improve transient control performances such as small rise time, small overshoot, small settling time, etc. A secondary stage, a platform, actuated by a pair of electro-magnets is mounted on a conventional elevation gimbal. In this mechanism, the gimbal provides large range but slow motion and the platform provides small range but fast positioning. A sliding mode control is applied to the platform positioning to attain robust performances and stability in the presence of the disturbance related to dynamic coupling of the gimbal and the platform. Results from experiments illustrate that the suggested dual stage mechanism controlled by the sliding mode control is effective in improving transient responses and attenuating the disturbance related with dynamic coupling.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.101-111
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• 2011

Most researches in WSN-based parking management system used wireless sensors to monitor the events in a car parking area. However, the problem of car collisions in car parks was not discussed by previous researches. The car position details over time are vital in analyzing a collision event. This paper proposes a collision verification method to detect and to analyze the collision event in the parking area, and then notifies car owners. The detection uses the information from motion sensors for comprehensive details of position and direction of a moving car, and the verification processes an object tracking technique with a fast OBB intersection test. The performance tests show that the location technique is more accurate with additional sensors and the OBB collision test is faster compared to a normal OBB intersection test.

• Aerospace Engineering and Technology
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• v.10 no.1
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• pp.45-53
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• 2011

This paper is technical review about Direct Sequence Spread Spectrum(DSSS) to apply in launch vehicle system. First, we introduce communication protocol(carrier frequency, code length, process gain, data rate, chip rate etc) about several application system using DSSS. And then, we survey and summarize the effect of doppler shift to the DSSS. The doppler shift is important error factor for PN code tracking in the fast moving system like launch vehicle. So, spread spectrum code acquisition technique for a direct sequence system in the presence of doppler effect must be investigated.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.552-554
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• 1998

In target tracking problems the fixed gain Kalman filter is primarily used to predict a target state vector. This filter, however, has a poor precision for maneuvering targets while it has a good performance for non-maneuvering targets. To overcome the problem this paper proposes the system which estimates the acceleration with neural networks using the input estimation technique. The ability to efficiently fuse information of different forms is one of the major capabilities of trained multi-layer neural networks. The primary motivation for employing neural networks in these applications comes from the efficiency with which more features can be utilized as inputs for estimating target maneuvers. The parallel processing capability of a properly trained neural network can permit fast processing of features to yield correct acceleration estimates. The features used as inputs can be extracted from the combinations of innovation data and heading changes, and for this we set the two dimensional model. The properly trained neural network system outputs the acceleration estimates and compensates for the primary Kalman filter. Finally the proposed system shows the optimum performance.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.211-217
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• 2011

This paper proposes a quasi-optimal linear DOA (Direction-of-Arrival) estimator which is necessary for the development of a real-time robot auditory system tracking moving acoustic source. It is well known that the use of conventional nonlinear filtering schemes may result in the severe performance degradation of DOA estimation and not be preferable for real-time implementation. These are mainly due to the inherent nonlinearity of the acoustic signal model used for DOA estimation. This motivates us to consider a new uncertain linear acoustic signal model based on the linear prediction relation of a noisy sinusoid. Using the suggested measurement model, it is shown that the resultant DOA estimation problem is cast into the NCRKF (Non-Conservative Robust Kalman Filtering) problem [12]. NCRKF-based DOA estimator provides reliable DOA estimates of a fast moving acoustic source in spite of using the noise-corrupted measurement matrix in the filter recursion and, as well, it is suitable for real-time implementation because of its linear recursive filter structure. The computational efficiency and DOA estimation performance of the proposed method are evaluated through the computer simulations.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.67-69
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• 2007

PMSM (Permanent Magnet Synchronous Motor) current control is a most inner loop of electromechanical driving systems and it plays a foundation role in the hierarchy's control loop of several mechanical machine systems. In this paper, a simple RMRAC control scheme for the PMSM is proposed in the synchronous frame. In the synchronous current model, the input signal is composed of as a calculated voltage by adaptive laws and system disturbances. The gains of feed-forward and feed-back controller are estimated by the proposed e-modification methods respectively, where the disturbances are assumed as filtered current tracking errors. After the estimation of the disturbances from the tracking errors, the corresponding voltage is fed forward to control input to compensate for the disturbances. The proposed method is robust to high frequency disturbances and has a fast dynamic response to time varying reference current trajectory. It also shows a good real-time performance duo to it's simplicity of control structure. Through the simulations considering several cases of external disturbances and experimental results, efficiency of the proposed method is verified

• KSCI Review
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• v.15 no.1
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• pp.53-64
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• 2007

Avoid at damage systems in order to avoid own IP address exposure, and an invader does not attack directly a system in recent hacking accidents at these papers, and use Stepping stone and carry out a roundabout attack. Use network audit Policy and use a CIS, AIAA technique and algorithm, the Sleep Watermark Tracking technique that used Thumbprints Algorithm, Timing based Algorithm, TCP Sequence number at network bases, and Presented a traceback system at TCP bases at log bases, and be at these papers Use the existing algorithm that is not one module in a system one harm for responding to invasion technology develop day by day in order to supplement the disadvantage where is physical logical complexity of configuration of present Internet network is large, and to have a fast technology development speed, and presentation will do an effective traceback system.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.4
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• pp.137-143
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• 2021

We propose an adaptive non-singular terminal sliding-mode control for the fast finite-time convergence (FANTSMC) in robot manipulator. The proposed FANTSMC approach is developed to be applied without singularity in robot manipulator, which has a new pole-placement control with the non-singular terminal sliding variable while generating the desirable control torque. Moreover, the switching gain is designed to suppress the time-delayed estimation error appropriately, which aims at providing the high robust tracking performance. Also, the proposed one employs one-sample delayed information to cancel out the system uncertainties and disturbances. For these reasons, it offers strong attraction within the finite time. It is shown that the tracking performance of the proposed FANTSMC approach is guaranteed to be uniformly ultimately bounded through the Lyapunov stability. The effectiveness of the proposed FANTSMC approach is illustrated in simulations, which is compared with that of the up-to-date control approach.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.1-20
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• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.