• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2135-2137
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• 2002

In this paper to overcome drawback of FLC an adaptive fuzzy sliding mode controller is proposed. The fuzzy basis function to describe the fuzzy system is introduced. The system parameter in sliding mode are estimated by the indirect adaptive fuzzy control. Adaptive laws for fuzzy parameters and fuzzy rule structure are established so that the whole system is suable in the sense of Lyapunov stability. The computer simulation results for inverted pendulum system show the performance of the proposed fuzzy sliding mode controller.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1081-1087
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• 2006

Generally, biped walking is difficult to control because a biped robot is a nonlinear system with various uncertainties. In this paper, we propose a hybrid sliding-mode control method using a WNN uncertainty observer for stable walking of the 5-link biped robot with model uncertainties and the external disturbance. In our control system, the sliding mode control is used as main controller for the stable walking and a wavelet neural network(WNN) is used as an uncertainty observe. to estimate uncertainties of a biped robot model, and the error compensator is designed to compensate the reconstruction error of the WNN. The weights of WNN are trained by adaptation laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified through computer simulations.

• Journal of KIEE
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• v.11 no.1
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• pp.62-68
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• 2001

In this paper it is proposed an advanced modified sliding mode control of a rotor field oriented control of induction motor. The application of this unconventional control has very good results, such as disturbance rejection and nice dynamic properties. Stability can be guaranteed even in the worst situation. A conventional "sliding mode" controller is characterised by fast switching control signal, which causes the chattering of the drive system. To overcome this problem, a modified law is used, by introducing a hysteresis band and a continuous control, which modifies the conventional law. The control is accomplished with dual TMS320C44 floating-point digital signal processor. The validity of the proposed method was verified by experiment on the propulsion system simulator, used for the development of Korean High-Speed Railway Train(KHSRT).in(KHSRT).

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.615-620
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• 2001

This paper addresses the design of sliding model fuzzy-model-based controller using genetic algorithms. In general, the construction of fuzzy logic controllers has difficulties for the lack of systematic design procedure. To release this difficulties, the sliding model fuzzy-model-based controllers was presented by authors. In this proposed method, the fuzzy model, which represents the local dynamic behavior of the given nonlinear system, is utilized to construct the controller. The overall controller consists of the local compensators which compensate the local dynamic linear model and the feed-forward controller which is designed via sliding mode control theory. Although, the stability and the performance is guaranteed by the proposed method, some design parameters have to be chosen by the designer manually. This problem can be solved by using genetic algorithms. The proposed method tunes the parameters of the controller, by which the reasonable accuracy and the control effort is achieved. The validity and the efficiency of the proposed method are verified through simulations.

• International Journal of Precision Engineering and Manufacturing
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• v.2 no.3
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• pp.34-40
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• 2001

Robot manipulator has highly nonlinear dynamics. Therefore the control of multi-link robot arms is a challenging and difficult problem. In this paper a decentralized adaptive fuzzy sliding mode scheme is developed for control of robot manipulators. The proposed scheme does not require an accurate manipulator dynamic model, yet it guarantees asymptotic trajectory tracking despite gross robot parameter variations. Numerical simulation for decentralized control of a 3-axis PUMA arm will also be included.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.125-130
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• 2009

A robust friction compensation scheme is proposed in this paper. The recurrent fuzzy neural network and friction parameter observer are developed with sliding mode based controller in order to obtain precise position tracking performance. For a servo system with incomplete identified friction parameters, a proposed control scheme provides a satisfactory result via some experiment.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.461-461
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• 2000

Nonlinear pulse width modulation(PWM) controlled system is considered to achieve control performance of thruster-controlled spacecraft. The actual PWM controlled motions occurs, very closely, around the average model rajectory. Furthermore nonlinear PWM controller design can be directly applied to thruster controlled spacecraft to determine thruster on-time. Sliding mode control for attitude tracking of three-axis thruster-controlled spacecraft is presented. Simulation results are shown which use modified Rodrigues parameters and sliding mode control law to achieve attitude tracking of a three-axis spacecraft with thrusters.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1738-1743
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• 2004

This paper presents an automobile traction control system by using a sliding mode controller with disturbance observer for estimating the car-body speed. First, we show that the control system, which combines an automobile system and a disturbance observer, can be divided into a controllable system and an estimated one. And, we found out that the effect of the traction control and ABS depends on the air resistance of the car. Then, the sliding mode control system is designed using the obtained combined system. And finally, the stability of this control system is verified by simulation and it shows a very satisfactory results.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.231-235
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• 1988

In this paper we present a new method to control system design using a sliding mode. The objective of this research is to develop the algorithm for the sliding mode control which is able to remove the chattering phenomena and to reduce the reaching phase. To accomplish this approach we introduce switching dynamics instead of switching logics to obtain the sliding mode. Consequently, we can obtain the new design approach which is much simpler than the VSS theory. And there do not exist chattering phenomena in this method because the obtained control input are continuous. Simultaneously we can reduce the reaching phase by a suitable choice of design factor. Numerical examples are discussed as illustration.

• Smart Structures and Systems
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• v.11 no.6
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• pp.569-587
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• 2013

This paper evaluates the closed loop performance of the reaching law based discrete sliding mode controller with multisensor data fusion (MSDF) in real time, by controlling the first two vibrating modes of a piezo actuated structure. The vibration is measured using two homogeneous piezo sensors. The states estimated from sensors output are fused. Four fusion algorithms are considered, whose output is used to control the structural vibration. The controller is designed using a model identified through linear Recursive Least Square (RLS) method, based on ARX model. Improved vibration suppression is achieved with fused data as compared to single sensor. The experimental evaluation of the closed loop performance of sliding mode controller with data fusion applied to piezo actuated structure is the contribution in this work.