• Proceedings of the KIEE Conference
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• 2006.04b
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• pp.229-231
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• 2006

The paper presents a sensorless speed control of interior permanent magnet synchronous motors using an adaptive integral binary observer 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 with 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 dynamic to the switching hyperplane equation.

• Journal of Power System Engineering
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• v.19 no.4
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• pp.89-96
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• 2015

This paper investigates some strategies to overcome the chattering problem of the conventional sliding mode observer (SMO) and to improve the rotor position estimation performance for full range sensorless control of a PMSM. An adaptive observer gain based on the Lyapunov's stability criterion and a cascade low pass filter with advanced phase delay compensation were proposed to reduce the chattering problem and to strengthen the filtering capability of the SMO. Several cases studies through experiments were carried out to confirm conventional SMO's problems and effectiveness of the proposed strategies. The experimental results show that the proposed method gives precise estimation on speed and rotor position when the motor rotates on 2% of its rated speed.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2057-2059
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• 2001

A nonlinear adaptive speed controller is designed for induction motors. Only the measurement of the stator current is used to design the controller and the observers. The sliding mode cascade observer is introduced to estimate the stator current and its time derivatives. The open-loop observer are designed to estimate the rotor flux and its time derivatives. The adaptive observer is also designed to estimate the rotor resistance. Sequentially, the rotor speed can be calculated using these estimated values. It is shown that the estimation errors of the corresponding states and the parameter converge to the specified residual set. It is also shown that the speed controller using these estimates is performed well. The experimental results are represented to investigate the validity of the proposed observer and controller.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.216-218
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• 1995

In this article a neural network adaptive observer is proposed and applied to the case of induction motor control. The high performance vector control drives require exact knowledge of rotor flux. Because rotor time constant is needed to observe rotor flux, the accurate estimation of rotor time constant is important. For these problems, proposed observer which comprises neural network flux observer and neural network torque observer is trained to learn the flux dynamics and torque dynamics and subject to further on-line training by means of a backpropagation algorithem. Therefore it has been shown that the robust control of induction motor neglects the rotor time constant variations.

• Journal of Mechanical Science and Technology
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• v.18 no.4
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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.

• Smart Structures and Systems
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• v.29 no.4
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• pp.617-624
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• 2022

A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.2
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• pp.168-175
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• 2009

This paper proposes an enhanced algorithm for sensorless control of 45,000rpm/22kw type Permanent Magnetic Synchronous Motor (PMSM) with air-foil bearing. The proposed algorithm is based on iterative adaptive flux observer for sensorless control of the motor in wide speed range by on-line estimating angle and velocity of rotor. Simulation error between actual and estimated angle of rotor is analyzed to enhance characteristics of frequency response of conventional adaptive flux observer, which results in stable response in wide range of speed. Using the iteration number for stable phase-delay characteristics, the observer enhances the dynamic characteristics of the observer within current control period. The experiment results show the reliable performance of the proposed algorithm through starting to high speed operating range.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.734-738
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• 1996

An adaptive output feedback controller is designed for tracking control of an n-link robot manipulator with unknown load. High-gain observers with same structure as error dynamic systems are used to estimate joint velocities. The parameter adaptation is achieved by the smoothed projection algorithm. The control inputs are saturated outside a domain of interest. Simulation results on a 2-link manipulator illustrate that when the speed of the high-gain observer is sufficiently high, the proposed controller recovers the performance under state feedback control.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1081-1084
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• 1991

A technique of indirect adaptive control based on certainty equivalence for input output linearization of nonlinear system is proven convergent by Teel. It incorporates an adaptive observer for identifying unknown system states and parameters and input-output linearizing controller for robust tracking. In this study, we show that robustness and tracking performances are improved considerably by using its normalized form of Teel's observer-based identifier. Simple examples are presented as illustration.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1081-1082
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• 2008

This paper presents adaptive fuzzy control based on observer for nonlinear HVAC system whose states are not available. Fuzzy systems are employed to approximate the unknown nonlinear functions of the HVAC system and the state observer is designed for estimating the states of the HVAC system. An adaptive fuzzy controller is firstly constructed without the controller singularity problem. The obtained control system shows robustness and effectiveness compared with classical feedback controller. Simulation results are provided to illustrate the control performance.