• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.227-230
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• 1990

In this paper we present a variable structure systeme-model following adaptive control (VSS-MFAC) method for an uncertain turbo-generator system which is apt to suffer from the unmodeled parameter uncertainties and the external disturbances. The simulation results for the power system stabilizer(PSS) exhibit robust adaptive model-following properties well in the PSS designed by the proposed VSS-MFAC methodology when a step change in the mechanical torque and a parameter variation is applied.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.273-275
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• 1992

A dynamic system containing uncertain elements is considered. The upper bound of the values of these uncertainties is estimated. Using the estimated value a bounded error state feedback control is proposed based on Corless and Leitmann's result [1].

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.113.5-113
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• 2001

In this work, we consider the flexible manipulator system. Generally, the manipulator system may often be made on the base of the imperfect modeling, joint friction, payload change, and external disturbances. These elements are uncertain factors. These uncertainties and flexibility make difficult to control the system. To overcome these defects, a class of robust control law is proposed for the flexible manipulator system and the singular perturbation approach is applied. To show the effectiveness of this control law, simulation is presented for one degree of freedom flexible joint and flexible link system.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.299-304
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• 1988

This paper describes the application of the variable structure control(VSC) concept for the position control of electro-hydraulic servomtor system. The basic philosopy of VSC is that the structure of the feedback control is altered as the state crosses discontinuity surfaces in the state surface with the result that certain desirable properties are achieved. The switching of the control function yields total(or selective) invariance to system parameter variations and disturbances, and closed loop eigen value placement in time-varing and uncertain systems.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.14-19
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• 1997

In this paper, a new fuzzy sliding mode control algorithm is presented for trajectory control of robot manipulators. A fuzzy logic is applied to a sliding mode control algorithm to have the sliding mode gain adjusted continuously through fuzzy logic rules. With this scheme, te stability and the robustness of the proposed fuzzy logic control algorithm are proved and ensured by the sliding mode control law. The fuzzy logic controller requires only a few tuning parameters to adjust. Computer simulation results are given to show that the proposed algorithm can handle uncertain systems with large parameter uncertainties and external disturbances.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.1
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• pp.136-144
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• 2004

In general a hydraulic system which uses a single rod hydraulic as an actuator is modeled as a nonlinear system and reveals uncertain Parameter characteristics such as the density variation of hydraulic oil and is subject to load variations and severe disturbances during operation. A variable design-parameter fuzzy PID controller is adopted to solve these undesirable internal and external problems and its effectiveness is verified through computer simulations for control performance and real time control possibility.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.77.3-77
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• 2001

An extended robust H$\infty$ filter is proposed for a nonlinear uncertain system. We also analyze the characteristics of the proposed filter such as an H$\infty$ performance criterion using the Lyapunov function method. The analysis results show that proposed filter has a robustness against disturbances such as process and measurement noises and against parameter uncertainties. Then the in-flight alignment for a strapdown inertial navigation system is designed using the presented filter. Simulation results show that the proposed filter effectively improve the performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.4
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• pp.343-352
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• 2016

A multi-rotor vehicle is an unmanned vehicle consisting of multiple rotors. A multi-rotor vehicle can be categorized as tri-, quad-, hexa-, and octo-rotor depending on the number of the rotors. Multi-rotor vehicles have many advantages due to their agile flight capabilities such as the ability for vertical take-off, landing and hovering. Thus, they can be widely used for various applications including surveillance and monitoring in urban areas. Since multi-rotors are subject to uncertain environments and disturbances, it is required to implement robust attitude stabilization and flight control techniques to compensate for this uncertainty. In this research, an advanced nonlinear control algorithm, i.e. sliding mode control, was implemented. Flight experiments were carried out using an onboard flight control computer and various real-time autonomous attitude adjustments. The feasibility and robustness for flying in uncertain environments were also verified through real-time tests based on disturbances to the multi-rotor vehicle.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.1
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• pp.101-111
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• 1993

Many processes such as machining, injection-moulding and metal-forming are usually operated by hydraulic servo-systems. The dynamic characteristics of these systems are complex and highly non-linear and are often subjected to the uncertain external disturbances associated with the processes. Consequently, the conventional approach to the controller design for these systems may not guarantee accurate tracking control performance. An effective neuro-fuzzy controller is proposed to realize an accurate hydraulic servo-system regardless of the uncertainties and the external disturbances. For this purpose, first, we develop a simplified fuzzy logic controller which have multidimensional and unsymmetric membership functions. Secondly, we develop a neural network which consists of the parameters of the fuzzy logic controller. It is show that the neural network has both learning capability and linguistic representation capability. The proposed controller was implemented on a hydraulic servo-system. Feedback error learning architecture is adopted which uses the feedback error directly without passing through the dynamics or inverse transfer function of the hydraulic servo-system to train the neuro-fuzzy controller. A series of simulations was performed for the position-tracking control of the system subjected to external disturbances. The results of simulations show that regardless of inherent non-linearities and disturbances, an accuracy tracking-control performance is obtained using the proposed neuro-fuzzy controller.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.6
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• pp.39-51
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• 1996

In the turning maneuver of the vehicle, its motion is mainly dependent on the genuine steering characteristics in view of the directional stability for stable turning ability. The under steer vehicle has an ability to maintain its own directonal performance for unknown external disturbances to some extent. From a few years ago, in order to acquire the more enhanced handling performance, some types of four wheel steering vehicle were considered and constructed. And, various rear wheel control logics for external disturbances has not been suggested. For this reason, in this posed rear wheel control logic is based on the yaw rate feed back type and is slightly modified by an yaw rate tuning factor for more stable turning performance. And an external disturbance is defined as a motivation of the additional yaw rate in the center of gravity by an uncertain input. In this study, an external disturbance is applied to the vehicle as a form of the additional yawing moment. Finally, the proposed rear wheel control logic is tested on the multi-body analysis software(ADAMS). J-turn and double lane change test are performed for the validation of the control logic.