• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.556-564
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• 2007

This paper proposes an efficient scheme to track a time variant channel induced by multi-path Rayleigh fading in mobile MIMO-OFDM systems with null sub-carriers. The proposed adaptive channel tracking scheme removes in the frequency domain the interfering signals of the other transmit (Tx) antennas by using a predicted channel frequency response before starting the channel estimation. Time domain channel estimation is then performed to reduce the additive white Gaussian noise (AWGN). The simulation results show that the proposed method is better than the conventional channel tracking method [3] in time varying channel environments. At a Doppler frequency of 300 Hz and bit error rates (BER) of 10-3, signal-to-noise power ratio (Eb/N0) gains of about 2.5 dB are achieved relative to the conventional channel tracking method [3]. At a Doppler frequency of 600 Hz, the performance difference between the proposed method and conventional one becomes much larger.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.264-269
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• 2002

In this paper, Η$_{\infty}$ depth and course controller of an AUV(Autonomous Underwater Vehicle) using Η$_{\infty}$ servo control is proposed. The Η$_{\infty}$ servo problem is formulated to design the controllers satisfying a robust tracking property with modeling errors and disturbances. The solution of the Η$_{\infty}$ servo problem is as fellows: first, this problem is modified as an Η$_{\infty}$ control problem for the generalized plant that includes a reference input mode, and then a sub-optimal solution that satisfies a given performance criteria is calculated by LMI(Linear Matrix Inequality) approach. The Η$_{\infty}$ depth and course controller are designed to satisfy with the robust stability about the modeling error generated from the perturbation of the hydrodynamic coefficients and the robust tracking property under disturbances(wave force, wave moment, tide). The performances of the designed controllers are evaluated with computer simulations, and finally these simulation results show the usefulness and application of the proposed Η$_{\infty}$ depth and course control system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.757-763
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• 2018

It is very difficult to achieve sufficient data rate and required quality of service due to the time-varying nature of the radio channel and various jammers such as path loss, delay, Doppler, shadowing and interference. Especially, the propagation path between the transmitting antenna and the tracking antenna mounted on the fuselage during the test and evaluation of the projectile system considered in this paper is based on the rapid movement of the projectile, the interference due to multipath fading due to the terrain, The propagation path may be blocked. In order to effectively improve the multipath fading occurring in the wireless communication system, a diversity combiner technique is required. In this paper, to derive the design and improvement schemes for the space diversity combiner technique among the diversity combiner schemes, the BER performance of maximum ratio combining (MRC) and selection combining (SC) In an adaptive SC / MRC diversity combiner that operates with MRC when it is lower than the specified threshold criterion when comparing the SNR between two signals received from the channel and operates with SC at high and combines the two received signals The BER performance of the system was compared and analyzed.

• Agricultural and Biosystems Engineering
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• v.6 no.2
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• pp.47-53
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• 2005

AMachine vision is a promising tool for the autonomous guidance of farm machinery. Conventional CCD camera for the machine vision needs a desktop PC to install a frame grabber, however, a web camera is ready to use when plugged in the USB port. A web camera with a notebook PC can replace existing camera system. Autonomous steering control system of this research was intended to be used for combine harvester. If the web camera can recognize cut/uncut edge of crop, which will be the reference for steering control, then the position of the machine can be determined in terms of lateral offset and heading angle. In this research, a white line was used as a cut/uncut edge of crop for steering control. Image processing algorithm including capturing image in the web camera was developed to determine the desired travel path. An experimental vehicle was constructed to evaluate the system performance. Since the vehicle adopted differential drive steering mechanism, it is steered by the difference of rotation speed between left and right wheels. According to the position of vehicle, the steering algorithm was developed as well. Evaluation tests showed that the experimental vehicle could travel within an RMS error of 0.8cm along the desired path at the ground speed of $9\sim41cm/s$. Even when the vehicle started with initial offsets or tilted heading angle, it could move quickly to track the desired path after traveling $1.52\sim3.5m$. For turning section, i.e., the curved path with curvature of 3 m, the vehicle completed its turning securely.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.301-303
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• 2001

This paper deals with the biped robot gait on changing the initial postures. Gait of a biped robot depends on the constraints of mechanical kinematics and initial posture. Also biped robot's dynamic walking stability is investigated by ZMP(Zero Moment Point). The path trajectory. with the knee joint bent like a human, is generated and applied with the above considerations. To decrease trajectory tracking error, in this paper, a new initial posture similar to bird's case is proposed and realized with the real robot.

• Journal of Drive and Control
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• v.12 no.2
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• pp.1-6
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• 2015

Recently, the Electro-Hydrostatic Actuator(EHA) has been developed as a result of research on energy saving. EHA is usually composed of a direct driven pump from an electric motor and is available to control cylinder displacement or velocity with high efficiency. In addition, it has the advantage of compactness, minimum leakage and availability of decentralized control. In this study, an EHA system was designed to decrease the path tracking error and manufactured for test. The linearization method provided in AMESim software was used to derive the model of EHA system. The derived model was applied to design the PI-D controller to effectively overcome the disturbance. The effectiveness of this controller was verified by further testing.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.400-402
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• 1997

This paper investigates the direct and adaptive control of mechatronic servo systems using modified chaotic neural networks (CNNs). For the performance evaluation of the proposed neural networks, we simulate the trajectory control of the X-Y table with direct control strategies. The CNN based controller demonstrates accurate tracking of the planned path and also shows superior performance on convergence and final error comparing with recurrent neural network(RNN) controller.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.1
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• pp.19-25
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• 1987

An optimal control procedure is presented for steering of an unmanned cart which has two motored wheels on its left and right side. Steering, running and stopping are enabled by controlling the motor speed independently. An optimal proportional-plus-integral control is employed to eliminate steady state error which is sustained by a simple proportional control for tracking a circular arc path. A simple and readily-implemented suboptimal control is also examined. The suboptimal control gives comparable performance and therefore provides an effective approach for industrial application of the unmanned cart. Effects of design parameters of unmanned cart such as forward velocity, wheel radius and position of sensor are investigated. It is shown that within the practicable values of the parameters the controlled performance improves rapidly with increase of those parameters then the improvement becomes negligible, which suggests base values over which the parameters should be taken.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1868-1870
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• 2006

Neural network is used in many fields of control systems, but input-output patterns of a control system are not easy to be obtained and by using as single feedback neural network controller. And also it is difficult to get a satisfied performance when the changes of rapid load and disturbance are applied. To resolve those problems, this paper proposes a new algorithm which is the neural network controller. The new algorithm uses the neural network instead of activation function to control object at the output node. Therefore, control object is composed of neural network controller unifying activation function, and it supplies the error back propagation path to calculate the error at the output node. As a result, the input-output pattern problem of the controller which is resigned by the simple structure of neural network is solved, and real-time learning can be possible in general back propagation algorithm. Application of the new algorithm of neural network controller gives excellent performance for initial and tracking response and it shows the robust performance for rapid load change and disturbance. The proposed control algorithm is implemented on a high speed DSP, TMS320C32, for the speed of 3-phase induction motor. Enhanced performance is shown in the test of the speed control.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.453-459
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• 2008

The neural network is currently being used throughout numerous control system fields. However, it is not easy to obtain an input-output pattern when the neural network is used for the system of a single feedback controller and it is difficult to obtain satisfactory performance with when the load changes rapidly or disturbance is applied. To resolve these problems, this paper proposes a new mode to implement a neural network controller by installing a real object for control and an algorithm for this, which can replace the existing method of implementing a neural network controller by utilizing activation function at the output node. The real plant object for controlling of this mode implements a simple neural network controller replacing the activation function and provides the error back propagation path to calculate the error at the output node. As the controller is designed using a simple structure neural network, the input-output pattern problem is solved naturally and real-time learning becomes possible through the general error back propagation algorithm. The new algorithm applied neural network controller gives excellent performance for initial and tracking response and shows a robust performance for rapid load change and disturbance, in which the permissible error surpasses the range border. The effect of the proposed control algorithm was verified in a test that controlled the speed of a motor equipped with a high speed computing capable DSP on which the proposed algorithm was loaded.