LPV $\mathcal {H}_\infty$ Control with Disturbance Estimation for Permanent Magnet Synchronous Motors

Lee, Youngwoo; Lee, Seung-Hi; Chung, Chung Choo

doi:10.1109/tie.2017.2721911

Cited by 48 publications

(27 citation statements)

References 28 publications

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“…Since further results is lacked about the influence of harmonics on system dynamics, it is difficult to quantify these effects on the system. The results in [20][21][22] indicate that the gain-scheduled controller design based on the this LPV model suffers less from the harmonics. Observer design as the dual problem of controller design is less dependent on the harmonic problem.…”

Section: Discussionmentioning

confidence: 91%

“…The influences of harmonics on system behavior need to be further discussed with respect to system parameter and dynamics variation. However, few results have been presented for dealing with this problem, even for the controller designs in [20][21][22]. Recalling the FDI schemes in…”

Section: Discussionmentioning

confidence: 99%

“…Since Equation (12) is an underdetermined equation, further constraints are required to solve this equation. In [20][21][22], a vertex expansion technique is presented to get a unique solution of η k . Furthermore, this work decomposes A (θ k ) with this method.…”

Section: Polytopic Decomposition Of the System Modelmentioning

confidence: 99%

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LPV Model Based Sensor Fault Diagnosis and Isolation for Permanent Magnet Synchronous Generator in Wind Energy Conversion Systems

et al. 2018

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This paper deals with the current sensor fault diagnosis and isolation (FDI) problem for a permanent magnet synchronous generator (PMSG) based wind system. An observer based scheme is presented to detect and isolate both additive and multiplicative faults in current sensors, under varying torque and speed. This scheme includes a robust residual generator and a fault estimation based isolator. First, the PMSG system model is reformulated as a linear parameter varying (LPV) model by incorporating the electromechanical dynamics into the current dynamics. Then, polytopic decomposition is introduced for H ∞ design of an LPV residual generator and fault estimator in the form of linear matrix inequalities (LMIs). The proposed gain-scheduled FDI is capable of online monitoring three-phase currents and isolating multiple sensor faults by comparing the diagnosis variables with the predefined thresholds. Finally, a MATLAB/SIMULINK model of wind conversion system is established to illustrate FDI performance of the proposed method. The results show that multiple sensor faults are isolated simultaneously with varying input torque and mechanical power.

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Section: Discussionmentioning

confidence: 91%

Section: Discussionmentioning

confidence: 99%

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LPV Model Based Sensor Fault Diagnosis and Isolation for Permanent Magnet Synchronous Generator in Wind Energy Conversion Systems

et al. 2018

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“…The associate editor coordinating the review of this manuscript and approving it for publication was Jun Shen . control strategies have been proposed to improve the control performance of PMSM, such as backstepping control [6], [7], finite time control [8], model predictive control [9], fuzzy logic control [10], sliding mode control (SMC) [11]- [13] and robust control [14]. Among them, SMC has been widely used for decades, because of its robustness and simplicity.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Super Twisting Nonlinear Fractional Order PID Sliding Mode Control of Permanent Magnet Synchronous Motor Speed Regulation System Based on Extended State Observer

et al. 2020

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In this article, a novel adaptive super-twisting nonlinear Fractional-order PID sliding mode control (ASTNLFOPIDSMC) strategy using extended state observer (ESO) for the speed operation of permanent magnet synchronous motor (PMSM) is proposed. Firstly, this paper proposes a novel nonlinear Fractional-order PID (NLFOPID) sliding surface with nonlinear proportion term, nonlinear integral term and nonlinear differential term. Secondly, the novel NLFOPID switching manifold and an adaptive supertwisting reaching law (ASTRL) are applied to obtain excellent control performance in the sliding mode phase and the reaching phase, respectively. The novel ASTNLFOPIDSMC strategy is constructed by the ASTRL and the NLFOPID sliding surface. Due to the utilization of NLFOPID switching manifold, the characteristics of fast convergence, good robustness and small steady state error can be ensured in the sliding mode phase. Due to the utilization of ASTRL, the chattering phenomenon can be weakened, and the characteristics of high accuracy and strong robustness can be obtained in the reaching phase. Further, an ESO is designed to achieve dynamic feedback compensation for external disturbance. Furthermore, Lyapunov stability theorem and Fractional calculus are used to prove the stability of the system. Finally, comparison results under different controllers demonstrate that the proposed control strategy not only achieves good stability and dynamic properties, but also is robust to external disturbance. INDEX TERMS Adaptive super-twisting nonlinear Fractional-order PID sliding mode control (ASTNL-FOPIDSMC) strategy, extended state observer (ESO), permanent magnet synchronous motor (PMSM), nonlinear Fractional-order PID (NLFOPID) sliding surface, adaptive super-twisting reaching law (ASTRL).

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“…A constrained state feedback speed control method was developed based on a model predictive approach [12]. A linear parameter varying H ∞ velocity control method was proposed to achieve robustness against disturbances [13]. Velocity control methods using direct torque control was designed for optimal dynamic performance [14].…”

Section: Introductionmentioning

confidence: 99%

Velocity Control for Ripple Reduction in Permanent Magnet Synchronous Motors With Low Performance Current Sensing

2020

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In this study, a velocity control method is proposed for minimizing velocity ripples in permanent-magnet synchronous motors with low-performance current sensing. The proposed method involves the use of desired currents, peak estimation, and a proposed tracking controller. The desired currents are used to achieve velocity control with only the current sensing. Peak estimation is performed to estimate the peak of the measured distorted current that occurs due to low-performance sensing. The proposed tracking controller is developed based on a proportional-integral controller using the estimated peak obtained from the measured currents. The proposed method aids in reducing velocity ripples and improving velocity tracking performance of permanent-magnet synchronous motors. The primary contribution of this method is the improvement of velocity-control performance with low-performance current sensing. The stability of the closed loop is proven by employing the input-to-state stable property. To verify the effectiveness of the proposed method, we performed simulations and experiments with different three cases. INDEX TERMS Velocity control, ripple reduction, peak estimation, low-performance current sensing, permanent-magnet synchronous motor.

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LPV $\mathcal {H}_\infty$ Control with Disturbance Estimation for Permanent Magnet Synchronous Motors

Cited by 48 publications

References 28 publications

LPV Model Based Sensor Fault Diagnosis and Isolation for Permanent Magnet Synchronous Generator in Wind Energy Conversion Systems

LPV Model Based Sensor Fault Diagnosis and Isolation for Permanent Magnet Synchronous Generator in Wind Energy Conversion Systems

An Adaptive Super Twisting Nonlinear Fractional Order PID Sliding Mode Control of Permanent Magnet Synchronous Motor Speed Regulation System Based on Extended State Observer

Velocity Control for Ripple Reduction in Permanent Magnet Synchronous Motors With Low Performance Current Sensing

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