• 전력전자학회:학술대회논문집
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• 전력전자학회 1998년도 Proceedings ICPE 98 1998 International Conference on Power Electronics
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• pp.125-130
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• 1998

This paper presents a speed control for ultrasonic motors using a PI controller and disturbance torque observer. Since the PI gains and the observer's poles are generally fixed, the control performance deteriorates when the driving conditions vary much. Therefore, we propose the speed control scheme that the PI gains and the observer's poles are adjusted on-line in accordance with the speed ripple using fuzzy reasoning.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.170-173
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• 2005

This paper presents an Fuzzy-Neuro Observer system for an ac servo motor dirve to track periodic commands using a neuro-fuzzy observer. AC servo motor drive system is rather similar to a linear system. However, the uncertainties, such as machanical parametric variation, external disturbance, uncertainty due to nonideal in transient state. therefore an intelligent control system that isan on-line trained neural network controller with adaptive learning rates.

• 전기학회논문지
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• 제66권11호
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• pp.1620-1627
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• 2017

In this paper, we design an observer-based $H_{\infty}$ fuzzy controller for interval type-2 Takagi-Sugeno (T-S) fuzzy systems under imperfect premise matching. The designed observer-based controller can effectively estimate the state of the system and make fuzzy system satisfy the $H_{\infty}$ disturbance attenuation performance. Using the slack matrix, the derived stabilization condition is expressed in terms of a linear matrix inequality. Finally, the effectiveness of the proposed method is verified through a simulation example.

• Journal of Information Processing Systems
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• 제18권4호
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• pp.510-523
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• 2022

Considering the problems of poor control effect, weak disturbance rejection ability and adaptive ability of two-wheeled self-balanced robot (TWSBR) systems on undulating roads, this paper proposes a fuzzy neural network active disturbance rejection controller (FNNADRC), that is based on fuzzy neural network (FNN) for online correction of active disturbance rejection controller (ADRC)'s nonlinear control rate. Firstly, the dynamic model of the TWSBR is established and decoupled, the extended state observer (ESO) is used to compensate dynamically and linearize the upright and displacement subsystems. Then, the nonlinear PD control rate and FNN are designed, and the FNN is used to modify the control parameters of the nonlinear PD control rate in real time. Finally, the proposed control strategy is simulated and compared with the traditional ADRC and fuzzy active disturbance rejection controller (FADRC). The simulation results show that the control effect of the proposed control strategy is slightly better than ADRC and FADRC.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 B
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• pp.925-926
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• 2006

This paper presents a sensorless speed control of an interior permanent magnet synchronous motor using an adaptive integral binary observer and fuzzy logic controller. In view of composition with a main loop regulator and an auxiliary loop regulator, the binary observer has a property of the chattering alleviation in the constant boundary layer. However, the steady state estimation accuracy and robustness are dependent upon the width of the constant boundary. In order to improve the steady state performance of the binary observer, the binary observer is formed by adding extra integral dynamics to the switching hyperplane equation. Also, because the conventional fixed gain PI controller are very sensitive to step change of command speed, parameter variations and load disturbance, the fuzzy logic controller is used to compensate a fixed gain PI controller. Therefore, a gain PI is fixed and the IPMSM is drived at another speed region. The effectiveness of the proposed the adaptive integral observer and the fuzzy logic controller are confirmed by experimental results.

• 한국정밀공학회지
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• 제18권10호
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• pp.161-167
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• 2001

This paper presents an approach to nonlinear engine idle controller and intake manifold absolute pressure(MAP) observer based on mean torque production model. A stable engine idle speed is important in that the unstable engine Idle mode can make engine to drooping or stall state. A sliding fuzzy controller has been designed to control engine idle speed under load disturbance. A sliding observer is also developed to estimate the intake manifold absolute pressure and compared with the actual MAP sensor value. The sliding mode observer has shown good robustness and good tracking performance. The inputs of sliding fuzzy controller are the errors of rpm and MAP. The output is a duty cycle(DC) for driving a idle speed control valve(ISCV).

• Journal of Mechanical Science and Technology
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• 제18권4호
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• pp.535-549
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• 2004

This paper proposes a sliding mode controller with fuzzy adaptive perturbation compensator(FAPC) to get a good control performance and reduce the chatter, The proposed algorithm can reduce the chattering because the proposed fuzzy adaptive perturbation compensator compensates the perturbation terms. The compensator computes the control input for compensating unmodeled dynamic terms and disturbance by using the observer-based fuzzy adaptive network(FAN) The weighting parameters of the compensate. are updated by on-line adaptive scheme in order to minimize the estimation error and the estimation velocity error of each actuator. Therefore, the combination of sliding mode control and fuzzy adaptive network gives the robust and intelligent routine to get a good control performance. To evaluate the control performance of the proposed approach, tracking control is experimentally carried out for the hydraulic motion platform which consists of a 6-DOF parallel manipulator.

• 제어로봇시스템학회논문지
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• 제17권11호
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• pp.1154-1158
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• 2011

In this paper, we discuss an observer-based fault tolerant controller design for the T-S (Takagi-Sugeno) fuzzy system with exogenous disturbance. To derive robust controller design conditions, we use $H_{\infty}$ design technique. The design conditions are derived in terms of linear matrix inequalities. An illustrative example is provided to show the effectiveness of the proposed methodology.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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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

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.117-123
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• 2001

To improve control performance of a non-linear system, many other reserches have used the sliding model control algorithm. The sliding mode controller is known to be robust against nonlinear and unmodeled dynamic terms. However, this algorithm raises the inherent chattering caused by excessive switching inputs around the sliding surface. Therefore, in order to solve the chattering problem and improve control performance, this study has developed the sliding mode controller with a perturbation estimator using the observer-based fuzzy adaptive network. The perturbation estimator based on the fuzzy adaptive network generates the control input of compensating unmodeled dynamics terms and disturbance. And the weighting parameters of the fuzzy adaptive network are updated on-line by adaptive law in order to force the estimation errors converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluation control performance of the proposed approach, tracking control simulation is carried is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.