• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2308-2310
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• 2001

In the adaptive fuzzy sliding mode control, from a set of a fuzzy IF-THEN rules adaptive fuzzy sliding mode control whose parameters are adjusted on-line according to some adaptation laws is constructed for the purpose of controlling the plant to track a desired trajectory. Most of the research works in nonlinear controller design using fuzzy systems consider the affine system with fixed grid-rule structure based on system state availability. The fixed grid-rule structure makes the order of the controller big unnecessarily, hence the on-line fuzzy rule structure and fuzzy observer based adaptive fuzzy sliding mode controller is proposed to solve system state availability problems. Therefore, adaptive laws of fuzzy parameters for state observer and fuzzy rule structure are established implying whole system stability in the sense of Lyapunov.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.67.2-67
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• 2001

In the adaptive fuzzy sliding mode control, from a set of fuzzy IF-THEN rules adaptive fuzzy sliding mode control whose parameters are adjusted on-line according to some adaptation laws is constructed for the purpose of controlling the plant to track a desired trajectory. Most of the research works in nonlinear controller design using fuzzy systems consider the affine system with fixed grid-rule structure based on system state availability. The fixed grid-rule structure makes the order of the controller big unnecessarily, hence the on-line fuzzy rule structure and fuzzy observer based adaptive fuzzy sliding mode controller is proposed to solve system state availability problems. Therefore adaptive laws of fuzzy parameters ...

• 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 Power Electronics
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• v.14 no.1
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• pp.105-114
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• 2014

The sliding mode control (SMC) strategy is applied to a permanent magnet synchronous machine vector control system in this study to improve system robustness amid parameter changes and disturbances. In view of the intrinsic chattering of SMC, a current sliding mode control method with a load sliding mode observer is proposed. In this method, a current sliding mode control law based on variable exponent reaching law is deduced to overcome the disadvantage of the regular exponent reaching law being incapable of approaching the origin. A load torque-sliding mode observer with an adaptive switching gain is introduced to observe load disturbance and increase the minimum switching gain with the increase in the range of load disturbance, which intensifies system chattering. The load disturbance observed value is then applied to the output side of the current sliding mode controller as feed-forward compensation. Simulation and experimental results show that the designed method enhances system robustness amid load disturbance and effectively alleviates system chattering.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.506-506
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• 2000

To improve control performance of a non-linear system, many other researches have used the sliding mode 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 generates the control input for 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 to converge to zero. Therefore, the combination of sliding mode control and fuzzy adaptive network gives rise to the robust and intelligent routine. For evaluating control performance of the proposed approach. tracking control simulation is carried out for the hydraulic motion simulator which is a 6-degree of freedom parallel manipulator.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2177-2178
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• 2011

In this paper, adaptive speed sensorless vector control, sliding mode observer to be present. Adaptive sliding mode observer of the motor stator coordinate system using the voltage equations of the rotor flux components are observed. Lyapunov function of the induction motor speed is estimated by the relationship further. In order to establish such a control scheme based on the way conventional PI controller and sliding mode observer annexing characteristics of the system through simulation and experiment were compared. Analyzed and compared according to the results presented confirmed the usefulness of the system.

• 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.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1276-1278
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• 2005

In this paper, we propose an adaptive sliding mode observer-based control of induction motors with uncertainties. The proposed adaptive sliding mode flux observer generates estimates both for the unknown parameters(load torque and rotor resistance) and for the unmeasured state variable (rotor fluxes); they converge to the corresponding true value under persistency of excitation which actually holds in typical operating conditions. The proposed controller guarantees speed tracking and bounded signals for every initial condition of the motor. Simulations show that all estimation errors tend quickly to zero so that high tracking performances are achieved both for speed and rotor flux.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.127-134
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• 2008

In this paper, we propose a robust adaptive backstepping control of induction motors with uncertainties using nonlinear disturbance observer(NDO). The proposed NDO is applied to estimate the time-varying lumped uncertainty which are derived from unknown motor parameters and load torque, but NDO error does not converge to zero since the derivate of lumped uncertainty is not zero. Then the fuzzy neural network(FNN) is presented to estimate the NDO error such that the rotor speed to converge to a small neighborhood of the desired trajectory. Rotor flux and inverse time constant are estimated by the sliding mode adaptive flux observer. Simulation results are provided to verify the effectiveness of the proposed approach.