• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1304-1316
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• 2018

An adaptive sliding-mode observer for speed estimation in sensorless vector controlled induction machine drives is proposed in this paper to balance the dilemma between the requirement of fast reaching transient and the chattering phenomenon reduction on the sliding-mode surface. It is well known that the sliding-mode observer (SMO) suffers from the chattering phenomenon. However, the reduction of the chattering phenomenon will lead to a slow transient process. In order to balance this dilemma, an adaptive exponential reaching law is introduced into SMO by optimizing the reaching way to the sliding-mode surface. The adaptive exponential reaching law is based on the options of an exponential term that adapts to the variations of the sliding-mode surface and system states. Moreover, the proposed sliding-mode observer considering adaptive exponential reaching law, which is called adaptive sliding-mode observer (ASMO), is capable for reducing the chattering phenomenon and decreasing the reaching time simultaneously. The stability analysis for ASMO is achieved based on Lyapunov stability theory. Simulation and experimental results both demonstrate the correctness and the effectiveness of the proposed method.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.311-317
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• 2023

This paper presents a sliding mode observer (SMO) for reconstructing cyber attacks affecting a system. The system is first re-expressed such that its design freedom is easier to manipulate. The SMO is then used to reconstruct the cyber attack affecting the system. A simulation example is used to verify the performance of the SMO under two types of cyber attacks, and its results demonstrate the effectiveness of our proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.256-263
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• 2010

The paper proposes a sensorless speed control strategy for a PMSM (Permanent Magnet Synchronous Motor) based on a new SMO (Sliding Mode Observer), which substitutes a signum function with a sigmoid function. To apply robust sensorless control of PMSM against parameter fluctuations and disturbance, the high speed SMO is proposed, which estimates the rotor position and angular velocity from the back EMF. The low-pass filter and additional position compensation of the rotor are used to reduce the chattering problem commonly found in sliding mode observer with signum function, which becomes possible by applying the sigmoid function with the control of a switching function. Also the proposed sliding mode observer with the sigmoid function has better efficiency than the conventional sliding mode observer since it adjusts the observer gain by variable boundary layer and estimates the stator resistance. The stability of the proposed sliding mode observer is verified by the Lyapunov second method in determining the observer gain. The validity of the proposed high speed PMSM sensorless velocity control has been demonstrated by real experiments.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.33-39
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• 2019

We propose a mechanical parameter estimation algorithm for surface-mounted permanent magnet synchronous motors (SPMSMs) using a sliding-mode observer (SMO) and an adaptive filter. The SMO estimates system disturbances in real time, which contain the information on mechanical parameters. A desirable feature that distinguishes the proposed estimation algorithm from other existing mechanical parameter estimators is that the adaptive filter estimates electromagnetic torque to improve the estimation performance. Moreover, the SMO acts as a low-pass filter to suppress the chattering effect, which enables the smooth output signals of the SMO. We verify the mechanical parameter estimation performance for SPMSM by conducting extensive experiments for the proposed algorithm.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1171-1173
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• 1997

This paper presents the sliding mode observer-model following(SMO-MF) power system stabilizer(PSS) for unmeasurable plant state variables. This SMO-MF PSS can be obtained by combining the sliding mode-model following(SM-MF) including closed-loop feedback(CLF) with the linear foil-order observer(LFOO).

• Journal of Power Electronics
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• v.15 no.6
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• pp.1559-1566
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• 2015

The brushless DC motor (BLDCM) has many advantages. As a result, it is widely used in electric vehicle (EV) drive systems. To improve the reliability of the motor control system, a position sensorless control strategy based on a sliding mode observer (SMO) is proposed. The global fast terminal sliding mode observer (GFTSMO) is proposed to enhance the control performance of the SMO control system. The advantages of the linear sliding mode and the nonsingular terminal sliding mode (NTSM) are combined in the control strategy. The convergence speed of the system state is enhanced. The motor commutation point is obtained with the observation of the back EMF, and the instantaneous torque value of the motor is calculated. Therefore, the position sensorless control of the BLDCM is realized. Experimental results show that the proposed control strategy can improve the convergence speed, dynamic characteristics and robustness of the system.

• 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.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.88-94
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• 1997

This paper presents the sliding mode observer-model following (SMO-MF) power system stabilizer(PSS) for unmeasurable state variables. This SMO-MF PSS is obtained by combining the sliding mode-model following (SM-MF) including closed-loop feedback(CLF) with the full-order observer(FOO). The control input of the proposed MO-MF PSS is derived by Lyapunov's second method to determine a control input that keeps the system stable for unmeasurable plant state variables. Simulation results show that the proposed SMO-MF PSS including CLF is able to reduce the low frequency oscillation and to achieve asymptotic tracking error between the reference mode state and the estimated plant state at different initial conditions.

• Journal of Electrical Engineering and information Science
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• v.2 no.4
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• pp.53-58
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• 1997

In this paper, the power system stabilizer(PSS) using the sliding mode observer-model following(SMO-MF) with closed-loop feedback (CLF) for single machine system is extended to multimachine system. This a multimachine SMO-MF PSS for unmeasureable plant state variable is obtained by combining the sliding mode-model following(SM-MF) including closed-loop feedback(CLF) with the full-order observer(FOO). And the estimated control input for unmeasurable plant sate variables is derived by Lyapunov's second method to determine a control input that keeps the system stable. Time domain simulation results for the torque angle and for the angular velocity show that the proposed multimachine SMO-MF PSS including CLF for unmeasurable plant sate variables is able to damp out the low frequency oscillation and to achieve asymptotic tracking error between the reference model state at different initial conditions and at step input.

• Proceedings of the KIPE Conference
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• 2013.11a
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• pp.200-201
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• 2013

This paper investigates a new approach for Li-Ion battery state-of-charge (SOC) estimation using sliding mode observer (SMO) technique including parameters aging compensation via recursive least squares (RLS). The main advantages of this approach would be low computational load, easiness of implementation along with the robustness of the method for internal battery model parameters estimation. The proposed algorithm was first tested on a set of acquired battery data using implementation in Simulink and later developed as C-code module for firmware application.