• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.293-295
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• 1995

In this article a fuzzy controller and neural network adaptive observer is proposed and applied to the case of induction motor control. The proposed observer which comprises neural network flux observer and neural network torque observer is trained to learn the flux dynamics and torque dynamics and subjected to further on-line training by means of a backpropagation algorithm. Therefore it has been shown that the robust control of induction motor neglects the rotor time constant variations.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.173-176
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• 2004

This paper is proposed to position and speed control of interior permanent magnet synchronous motor(SPMSM) drive without mechanical sensor. A adaptive fuzzy controller is applied for speed control of SPMSM drive A adaptive state observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of SPMSM, that employs a d-q rotating reference frame attached to the rotor. A adaptive observer is implemented to compute the speed and position feedback signal. The validity of the proposed sensorless scheme is confirmed by various response characteristics.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2901-2903
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• 2000

This thesis deals with study and implementation of Fuzzy controller with observer which can enhance the path-tracking performance of optically guided AGV(Automated Guided Vehicle). The AGV in this thesis is differential drive type and has front-side and rear-side optical sensors. which can identify the guiding path. This controller has excellent disturbance rejection and therefore is advantageous when it is instructed to follow straight paths. This fuzzy controller with observer enhances transient performance of the controller is demonstrated by simulation and is compared with that of individual loop controller

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.15-20
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• 2010

In this paper, we discuss a decentralized observer design problem for the fault detection in the large-scale continuous-time T-S (Takagi-Sugeno) fuzzy system. Since the fault detection residual is desired to be as sensitive as possible, on the fault, we use $\mathfrak{H}_-$ index performance criterion. Sufficient conditions for the existence of such a observer is presented in terms of linear matrix inequalities. Simulation results show the effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.506-511
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• 2006

This paper considers a method to design sliding mode observers for a class of uncertain systems using Linear Matrix Inequalities(LMI). In an LMI-based sliding mode observer design method for a class of uncertain systems the switching surface is set to be the difference between the observer and system output. In terms of LMIs, a necessary and sufficient condition is derived for the existence of a sliding-mode observer guaranteeing a stable sliding motion on the switching surface. The gain matrices of the sliding-mode observer are characterized using the solution of the LMI existence condition. The results are illustrated by an example.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.484-487
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• 2003

In this paper describes a design of Adaptive high gain observer. The gain of the observer is properly set up using the fuzzy control and adaptive high gain observer that have a superior transient characteristic and is easy to implement compared the existing method is designed. In order to verify the performance of the Adaptive high gain observer which is proposed in this paper, it is compared estimate performance of High-gain Observer and Adaptive High Gain Observer with the computer simulation. Effectiveness of the proposed high gain observer is proved from the simulation to compare the case with a speed sensor to the case with Adaptive high gain observer in the speed control of DC servo motor.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.5
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• pp.343-351
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• 2010

This paper proposes a new fuzzy speed controller based on the Takagi-Sugeno fuzzy method to achieve a robust speed control of a permanent magnet synchronous motor (PMSM). The proposed controller requires the information of the load torque, so the second-order load torque observer is used to estimate it. The LMI condition is derived for the existence of the proposed fuzzy speed controller, and the gains of the controller are provided. It is proven that the augmented control system including the fuzzy speed controller and the load torque observer is exponentially stable. To evaluate the performance of the proposed fuzzy speed controller, the simulation and experimental results are presented under motor parameter variations. Finally, it is clearly verified that the proposed control method can accurately control the speed of a permanent magnet synchronous motor.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.6
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• pp.80-86
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• 2002

In this paper, we present a method of fuzzy controller design for the power plant superheater in the form of bilinear system. For the steam temperature control, the input variables are constructed by the area of difference between the profiles estimated from bilinear observer and reference profiles, and the time rate of change. We estimate the control rules by T. Takagi and M. Sugeno's fuzzy model. The feasibilities of the suggested method are illustrated via the computer simulation results.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

• Journal of Ocean Engineering and Technology
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• v.30 no.5
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• pp.405-414
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• 2016

This paper presents an internal oil leakage detection problem for a hydraulic single-rod cylinder. We derive the dynamics of the hydraulic cylinder as a state space model, and then design a T—S fuzzy model-based fault detection observer. We adopt an H_∞ observer design scheme so that the observer is robust against disturbance and relatively sensitive to the leakage fault. Sufficient design conditions are derived in the form of linear matrix inequalities. A numerical example is provided to verify the proposed techniques.