• International Journal of Automotive Technology
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• v.3 no.2
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• pp.79-88
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• 2002

Emergent Collision Avoidance Systems (CAS's) are beginning to assist drivers by performing specific tasks and extending the limits of driver's perception. As CAS's evolve from simple systems handling discrete tasks to complex systems managing interrelated driving tasks, the risk of failure from hidden causes greatly increases. The successful implementation of such a complex system depends upon a robust software architecture. Host of the difficulty in implementing system arises from interconnections between the components. The CAS architecture presented in this paper focuses on these interconnections to mitigate this problem. Moreover, by constructing the GAS architecture through the composition of existing architectural styles, the resulting system will exhibit predictable qualities. Some of the qualities represent limitations that translate into constraints on the system. Others are beneficial aspects that satisfy stakeholder requirements .

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.588-591
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• 1998

In this paper, we present a robust adaptive backstepping output feedback controller for nonlinear systems perturbed by unmodelled dynamics and disturbances. Especially, backstepping technique with modular approach is used to separately design controller and identifier. The design of identifier is based on the observer-based scheme which possesses a strict passivity property of observer error system. We will use Switching-${\sigma}$ modification at the update law and the modified control law to attenuate the effects of undodelled dynamics and disturbances for nonlinear systems.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.791-794
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• 1995

This paper introduces a new approach to adaptive control using a combination of direct, indirect and variable structrure method. A new variable structrue input is derived to counteract the effects of disturbances. Direct input is used to have fast response and indirect input improves the transient behavior of the system. Computer simulation results illustrate the very satisfactory performance of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.285-288
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• 2005

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose a neuro-adaptive controller for robot manipulators using the radial basis function network(RBFN) that is a kind of a neural network. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between the actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that the parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed neuro-adaptive controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.1
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• pp.104-111
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• 2000

It is very difficult to maintain the desired tank level without any overflow or any shortage in a dangerous shemical plant and in a cooling one. Futhermore, because its dynamics are very complicate and nonlinear, it is impossible to realize the precise control using the accurate mathematical model which can be applied to the various peration modes. Nonetheless, the sliding mode controller(SMC) is known as having the robust variable structures for the nonlinear control system with the parametric perturbations and with the rapid disturbances. But the adaptive tuning algorithms for their parameters are not satisfactory. Therefore, in this paper, a Real Variable Elitist Genetic Algorithm based Sliding Mode Controller (RVEGA SMC) for the precise control of the coupled tank level was tried. The SMC's switching parameters were optimized easily and rapidly by RVEGA. The simulation results showed that the tank level could be satisfactorily controlled without and overshoot and any steady-state error by the proposed RVEGA SMC.

• Proceedings of the KIPE Conference
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• 2014.11a
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• pp.66-67
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• 2014

Stabilization of the DC bus voltage is an important task in DC-AC microgrid system with renewable energy source such as solar system. A battery energy storage system (BESS) has become a general solution to stabilize the DC-bus voltage in DC-AC microgrid. This paper develops the analog BESS controller which requires neither computation nor dc-bus voltage measurement, so that the system can be implemented simply and easily. Even though others methods can stabilize and control the DC-bus voltage, it has complicated structure in control and low adaptive capability. The proposed topology is simple but is able to compensate the solar source variation and stabilize the DC-bus voltage under any loads and distributed generation (DG) conditions. In addition, the design of analog controller is presented to obtain a robust system. In order to verify the effectiveness of the proposed control strategy, simulation is carried out by using PSIM software.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.982-984
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• 1999

For active noise control system, one would choose one of two methods: Fixed control design and Adaptive filter design. Each one has its own advantages. But fixed controller design method prefer for active noise control in a small cavity system. In this paper, we design a controller for the small cavity system using CDM and compare controller using CDM with $H{\infty}$. The order of the resulting controller is lower than that of the robust $H{\infty}$ design, which means CDM will be more prefer for implementation purpose designs.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.285-291
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• 2008

Active Queue Management(AQM) has been widely used for congestion avoidance in Transmission Control Protocol(TCP) networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level, most of them are incapable of adequately adapting to TCP network dynamics due to TCP's non-linearity and time-varying stochastic properties. To alleviate these problems, we introduce an AQM technique based on a dynamic neural network using the Back-Propagation(BP) algorithm. The dynamic neural network is designed to perform as a robust adaptive feedback controller for TCP dynamics after an adequate training period. We evaluate the performances of the proposed neural network AQM approach using simulation experiments. The proposed approach yields superior performance with faster transient time, larger throughput, and higher link utilization compared to two existing schemes: Random Early Detection(RED) and Proportional-Integral(PI)-based AQM. The neural AQM outperformed PI control and RED, especially in transient state and TCP dynamics variation.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.83-90
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• 2004

In this paper we present a new real-time visual servoing unit for laparoscopic surgery This unit can automatically control laparoscope manipulator through visual tracking of laparoscopic surgical tool. For the tracking, we present two-stage adaptive CONDENSATION(conditional density propagation) algorithm to extract the accurate position of the surgical tool tip from a surgical image sequence in real-time. This algorithm can be adaptable to abrupt change of laparoscope illumination. For the control, we present virtual damper system to control a laparoscope manipulator safely and stably. This system causes the laparoscope to move under constraint of the virtual dampers which are linked to the four sides of image. The visual servoing unit operates the manipulator in real-time with locating the surgical tool in the center of image. The experimental results show that the proposed visual tracking algorithm is highly robust and the controlled manipulator can present stable view with safe.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1101-1107
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• 2017

In this paper, a robust and fast grid synchronization method of a three-phase power converter is proposed. The amplitude and phase information of grid voltages are essential for power converters to be properly connected into the utility. The phase-lock-loop in synchronous reference frame has been widely adopted for the three-phase converter system since it shows a satisfactory performance under balanced grid voltages. However, power converters often operate under abnormal grid conditions, i.e. unbalanced by grid faults and frequency variations, and thus a proper active and reactive power control cannot be guaranteed. The proposed method adopts a second order generalized integrator in synchronous reference frame to detect positive sequence components under unbalanced grid voltages. The proposed method has a fast and robust performance due to its higher gain and frequency adaptive capability. Simulation and experimental results show the verification of the proposed synchronization algorithm and the effectiveness to detect positive sequence voltage.