• Journal of the Korean Society of Industry Convergence
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• v.19 no.2
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• pp.81-87
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• 2016

This paper presents a new approach to control of stable motion of single wheel driving robot system of a pitch that is controlled by an in-wheel motor and a roll that is controlled by a reaction wheel. This robot doesn'thave any actuator for a yaw axis control, which makes the derivation of the dynamics relatively simple. The Lagrange equations was applied to derive the dynamic equations of the one wheel driving robot to implement the dynamic speed control of the mobile robot. To achieve the real time speed control of the unicycle robot, the sliding mode control and optical regulator are utilized to prove the reliability while maintaining the desired speed tracking performance. In the roll controller, the sigmoid-function based robust controller has been adopted to reduce the vibration by the situation function. The optimal controller has been implemented for the pitch control to drive the unicycle robot to follow the desired velocity trajectory in real time using the state variables of pitch angle, angular velocity, angle and angular velocity of the driving wheel. The control performance of the control systems from a single dynamic model has been illustrated by the real experiments.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.259-266
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• 2015

This study presents new scheme for various walking pattern of biped robot under the limitted enviroments. We show that the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multilayer backpropagation neural network identification is simulated to obtain a learning control solution of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The main advantage of our scheme is that we do not require any knowledge about the system dynamic and nonlinear characteristic, and can therefore treat the robot as a black box. It is also shown that the neural network is a powerful control theory for various trajectory tracking control of biped robot with same learning-vase. That is, we do net change the control parameter for various trajectory tracking control. Simulation and experimental result show that the neural network is practically feasible and realizable for iterative learning control of biped robot.

• 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

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.5
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• pp.58-64
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• 2004

A new method to obtain approximate solutions by placing the only poles of the slow subsystem for the two-time-scale aircraft dynamic systems. The two kinds of approximate solutions are obtained by a matrix block diagonalization. One is called the uncorrected solution, and the other is called the corrected solution. The former has an error of $O({\varepsilon})$, and the latter has an error of $O({\varepsilon}^2)$. Of course, both solutions are robust enough even though they are reduced solutions. The excellence of the proposed method is illustrated by an numerical example of an aircraft longitudinal dynamics.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.11-19
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• 2010

Most of deblocking filters assumes that the block boundaries are accurately known and the coding information like quantization parameters are available. In some applications such as commercial television, however, many external video inputs without known block boundary and coding information arc given. If a decompressed video sequence heavily degraded with blocking artifacts is given through the external video port, it is absolutely necessary to detect block boundaries and control the strength of deblocking filtering by analysing the given images. This paper presents an efficient method to find the block boundaries and estimate the strength of the blocking artifacts without the knowledge of coding information. In addition, the confidence of the estimated blocking artifact information is also evaluated to control the adaptive deblocking filter robustly. Experiment results show that the estimated block boundary locations and strength relative strength and confidence information are practically good enough to reduce the blocking artifacts without prior knowledge.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.2 s.42
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• pp.37-46
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• 2005

To date, many viable smart base isolation systems have been proposed and investigated. In this study, a novel friction pendulum system (FPS) and an MR damper are employed as the isolator and supplemental damping device, respectively, of the smart base isolation system. A fuzzy logic controller (FLC) is used to modulate the MR damper because the FLC has an inherent robustness and ability to handle non linearities and uncertainties. A genetic algorithm (GA) is used for optimization of the FLC. The main purpose of employing a GA is to determine appropriate fuzzy control rules as well to adjust parameters of the membership functions. To this end, a GA with a local improvement mechanism is applied. This method is efficient in improving local portions of chromosomes. Neuro fuzzy models are used to represent dynamic behavior of the MR damper and FPS. Effectiveness of the proposed method for optimal design of the FLC is judged based on computed responses to several historical earthquakes. It has been shown that the proposed method can find optimal fuzzy rules and the GA optimized FLC outperforms not only a passive control strategy but also a human designed FLC and a conventional semi active control algorithm.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.6
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• pp.37-44
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• 1999

In this paper, we present a new sliding surface with a time-varying repeated root for fast and robust tracking of higher-order uncertain systems. The repeated root is moved to target one with stabilizing the closed-loop time-varying system in sliding mode. This initial root is obtained so that shifting distance of the surface may be minimized with respect to an initial error, and the intercept is produced so that the surface may pass the initial error. Under the allowable input, fast shifting of the surface and movement of the repeated root enable the error convergence rate to be increased. The proposed sliding mode control makes the error always remain on the surface from the beginning, and therefore, the system is more insensitive to parameter uncertainties and external disturbances. In simulation, the effectiveness of the proposed method is proved by comparison with the conventional one.