• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.119-122
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• 1995

Neural network has found wide applications in the system identification, modeling, and realization based on its function approximation capability. THe system governe dby nonlinear dynamics is hard to be identified by the neural network because there exist following difficulties. FIrst, the training samples obtained by the stae trajectory are apt to be nonuniform over the region of interest. Second, the system may becomje unstable while attempting to obtain the samples. This paper deals with these problems in discrete-time system and suggest effective solutions which provide stability and uniform sampliing by the virtue of robust control theory and heuristic algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.347-356
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• 1996

In this paper, we present the circular array structure for estimating the temporal and spatial specturm of multiple narrowband incoherent signals which have different frequencies. The conventional linear array is computationally demanding for simultaneously estimating the spatial and temporal spectrum since it requires the tapped delay line filer. The statistical performance of the circular array is never deteriorated eve though it requires much less computational load than the uniform linear array. Especially, it is shown that the circular array resolves the direction-of-arrivals of the multiple signals without the spatial and temporal aliasing the fundamental nonuniform-sampling property prossessed by it. Computer simulation results are shown to demonstrate the better performance achieved with the circular array geometry relative to that obtained with a uniform linear array with taps.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.5
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• pp.243-250
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• 2002

In the synthesis of the current source distribution function of an array antenna with the arbitrary radiation pattern, the Woodward-Lawson sampling method has been mainly used for the synthesis of an even function lobe pattern. In this paper, the method is extended to the synthesis of the odd function pattern and then the optimum synthesis method for the nonlinear source distribution function is proposed. The proposed method is applied to the design of nonuniform transmission lines with arbitrary reflection responses. The both dispersive impedance profiles of single and coupled nonuniform lines with arbitrary reflection responses are directly synthesized by the sampled values of a reflected spectral pattern which is optimally shaped by a perturbation of its complex null positions, hence removing the conventional step-by-step segmentation process and global optimization routines. The control problem in the case that all of port impedances are identical is also solved. The generality of the proposed method is verified by a filter design with the controlled arbitrary passband

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.312-321
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• 2003

In this paper, we implement robot which are ability to recognize obstacles and moving automatically to destination. we present two results in this paper; hardware implementation of image processing board and software implementation of visual feedback algorithm for a self-controlled robot. In the first part, the mobile robot depends on commands from a control board which is doing image processing part. We have studied the self controlled mobile robot system equipped with a CCD camera for a long time. This robot system consists of a image processing board implemented with DSPs, a stepping motor, a CCD camera. We will propose an algorithm in which commands are delivered for the robot to move in the planned path. The distance that the robot is supposed to move is calculated on the basis of the absolute coordinate and the coordinate of the target spot. And the image signal acquired by the CCD camera mounted on the robot is captured at every sampling time in order for the robot to automatically avoid the obstacle and finally to reach the destination. The image processing board consists of DSP (TMS320VC33), ADV611, SAA7111, ADV7l76A, CPLD(EPM7256ATC144), and SRAM memories. In the second part, the visual feedback control has two types of vision algorithms: obstacle avoidance and path planning. The first algorithm is cell, part of the image divided by blob analysis. We will do image preprocessing to improve the input image. This image preprocessing consists of filtering, edge detection, NOR converting, and threshold-ing. This major image processing includes labeling, segmentation, and pixel density calculation. In the second algorithm, after an image frame went through preprocessing (edge detection, converting, thresholding), the histogram is measured vertically (the y-axis direction). Then, the binary histogram of the image shows waveforms with only black and white variations. Here we use the fact that since obstacles appear as sectional diagrams as if they were walls, there is no variation in the histogram. The intensities of the line histogram are measured as vertically at intervals of 20 pixels. So, we can find uniform and nonuniform regions of the waveforms and define the period of uniform waveforms as an obstacle region. We can see that the algorithm is very useful for the robot to move avoiding obstacles.