A Model Reference Adaptive Control Based Speed Controller for a Surface-Mounted Permanent Magnet Synchronous Motor Drive

Nguyen, Anh Tuan; Rafaq, Muhammad Saad; Choi, Han Ho; Jung, Jin‐Woo

doi:10.1109/tie.2018.2826480

Cited by 100 publications

(75 citation statements)

References 30 publications

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“…Once the turbine power exceeds its rating, the error will command a change in blade pitch angle and make βref which results in the cut-down of energy absorption generally in controllers and actuator pitch angle limited to angles between 0 º and 90 º. (Nguyen et al 2018;Toulabi et al 2017). In this case, the pitch controller increases slowly and continuously the angle of the pitch to reduce the mechanical power generated by the turbine, thereby prevent the rotor speed up (Nguyen et al 2018).…”

Section: Pitch Control Modelmentioning

confidence: 99%

See 1 more Smart Citation

Intelligent Sliding Mode Adaptive Controller Design for Wind Turbine Pitch Control System Using PSO-SVM in Presence of Disturbance

Kamarzarrin

Refan

2020

J Control Autom Electr Syst

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Today, the generated electrical energy using renewable energy is rapidly growing all over the world. The speed and direction of the wind are fundamental parameters affecting on power production of wind turbine that is constantly changing. One of the methods for controlling wind turbine power is changing the angle of the blades. In this paper, an adaptive control method has been used to control the wind turbine pitch angle. The proposed method is based on sliding mode control, whose coefficients have been calculated using the particle swarm optimization-support vector machine method. In order to evaluate the effectiveness of the proposed method, it has been compared with the Model Reference Adaptive Controller (MRAC) in the operating under disturbance. The results show that the proposed controller has a better performance than that of the MRAC in the presence of disturbance. Simulations show that the produced power at different wind velocities has reached its optimum value faster.

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Section: Pitch Control Modelmentioning

confidence: 99%

“…(Nguyen et al 2018;Toulabi et al 2017). In this case, the pitch controller increases slowly and continuously the angle of the pitch to reduce the mechanical power generated by the turbine, thereby prevent the rotor speed up (Nguyen et al 2018).…”

Section: Pitch Control Modelmentioning

confidence: 99%

Intelligent Sliding Mode Adaptive Controller Design for Wind Turbine Pitch Control System Using PSO-SVM in Presence of Disturbance

Kamarzarrin

Refan

2020

J Control Autom Electr Syst

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“…The output feedback nonlinear H∞ controller [22] is designed for PMSM to achieve strong robustness and anti-fluctuation performance. In [23], the model reference adaptive control (MRAC) approach with a compensating control term is introduced to achieve rapid speed response and strong robustness. The compensating control term is added for the uncertainty of PMSM parameters in this method.…”

Section: Introductionmentioning

confidence: 99%

Speed Regulation Based on Adaptive Control and RBFNN for PMSM Considering Parametric Uncertainty and Load Fluctuation

et al. 2020

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A novel speed control scheme combining adaptive speed controller and radial basis function neural network (ASC-RBFNN) is proposed for the speed regulation of permanent magnet synchronous motor (PMSM) in this paper. On one hand, in order to reduce the effect of parametric uncertainty and complicated load fluctuation on the speed control performance, an ASC is proposed. Meanwhile, the speed control system (SCS) of PMSM with the proposed ASC is asymptotically stable even though the parametric uncertainty and complicated load fluctuation exist. On the other hand, with consideration of the uncertainty of complicated load, PMSM parameters, and ASC parameters, the RBFNN is used to optimize all ASC parameters for optimal speed control performance. Finally, the performance is verified on an experiment platform. The results indicate that the SCS with the ASC-RBFNN speed control scheme is with good system stability, fast speed response, and strong anti-fluctuation performance in whole-speed range.

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“…However, the parameters of the motor often fluctuate in a nonlinear manner during motor operation. To avoid the above-mentioned problems, the adaptive control algorithm has been proposed in [21][22][23]. Article [20] adopts an online identification method to combat the time-varying problem of motor parameters.…”

Section: Introductionmentioning

confidence: 99%

High-Precision Coordinated Position Control of Integrated Permanent Magnet Synchronous Linear Motor Stations

Pan

Niu

et al. 2020

IEEE Access

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In multi-station linear reciprocating processing systems, the positioning accuracy and the cooperative precision of the motion stations directly affect the production quality of products. This paper aims to enhance both the positioning and the coordination accuracy of the motion stations from the integrated permanent magnet synchronous linear motor (IPMSLM) stations during the reciprocating motions, especially in the presence of load disturbance. Firstly, the adaptive control strategy based on pole placement principle with online parameter identification is proposed for single IPMSLM station. The least squares identification algorithm with forgetting factor is employed to calculate the mathematic model online, so as to solve the problem that the IPMSLM stations cannot be accurately modeled with the existence of parameter perturbation and load disturbance. Secondly, in order to improve the coordination performance of the IPMSLM stations, the cooperative error equation is proposed, and a ring coupling cooperative (RCC) control strategy based on Lyapunov stability theorem is designed. The accuracy and effectiveness of this proposed collaborative control strategy is verified by experiments under no-load and spring-load conditions. Experimental results show that for the proposed adaptive and coordinate control strategy, the positioning error and the coordination error during the reciprocating motion can be guaranteed uniformly within ±8 μm and ±10 μm, respectively.

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A Model Reference Adaptive Control Based Speed Controller for a Surface-Mounted Permanent Magnet Synchronous Motor Drive

Cited by 100 publications

References 30 publications

Intelligent Sliding Mode Adaptive Controller Design for Wind Turbine Pitch Control System Using PSO-SVM in Presence of Disturbance

Intelligent Sliding Mode Adaptive Controller Design for Wind Turbine Pitch Control System Using PSO-SVM in Presence of Disturbance

Speed Regulation Based on Adaptive Control and RBFNN for PMSM Considering Parametric Uncertainty and Load Fluctuation

High-Precision Coordinated Position Control of Integrated Permanent Magnet Synchronous Linear Motor Stations

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