A High-efficiency PMSM Sensorless Control Approach Based on MPC Controller

Gao, Jinqiu; Liu, Jinglin; Gong, Chao

doi:10.1109/iecon.2018.8591305

Cited by 8 publications

(3 citation statements)

References 11 publications

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“…Gao et al proposed a new single-loop model predictive control (MPC) based on back-electromotive force and I-F control to simplify the system structure and control algorithm. It has a high dynamic and steady-state performance [12]. Zhang et al designed an asymmetric space vector modulation (ASVM) method to improve the calculated position estimate [13].…”

Section: Wave Generation and Ship Motion Coordinatementioning

confidence: 99%

Improved Fractional-Order PID Controller of a PMSM-Based Wave Compensation System for Offshore Ship Cranes

Chen

Wang

Benbouzid

et al. 2022

JMSE

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Wave compensation technology is crucial to the safety of the ship operation and the accurate placement of load. Its compensation efficiency and the gentle change of the rope tension are particularly important. In this paper, we adopt permanent magnet synchronous machine (PMSM) as the actuator to construct the basic wave compensation system. Firstly, the motion model of ship and load under wave action is established, and the fractional-order PID (FOPID) controller for the position loop of the PMSM is introduced. Then, the parameters of FOPID are optimized by genetic algorithm-particle swarm optimization (GAPSO) algorithm, which is based on genetic algorithms (GA) and particle swarm optimization (PSO) algorithms for better compensation performance. The wave synchronization strategy is used to simulate the load, when it needs to be taken into the water. The non-linear dynamic equations of the rope are solved by Lagrange mechanics and the heave displacement is obtained by time series prediction algorithm. Finally, the effect of wave compensation and wave synchronization strategy are verified on MATLAB/Simulink. The results show that after the compensation, the crane load can follow the set height value very well, the compensation efficiency can reach more than 94%, and the wave synchronization strategy significantly reduces the change of the rope tension.

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Section: Wave Generation and Ship Motion Coordinatementioning

confidence: 99%

Improved Fractional-Order PID Controller of a PMSM-Based Wave Compensation System for Offshore Ship Cranes

Chen

Wang

Benbouzid

et al. 2022

JMSE

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“…When the system parameters change, the output results of the PI controller will degrade dramatically. In order to enhance the capability of resisting disturbances, a sensorless MPC control method for PMSM [23] is developed based on a first-order Euler method. Then, by combining a back-EMF with an I-F control method, a new single-loop MPC is proposed, which merges the current loop and speed loop.…”

Section: Aims and Objectivesmentioning

confidence: 99%

New Adaptive Control Strategy for a Wind Turbine Permanent Magnet Synchronous Generator (PMSG)

et al. 2020

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Wind energy conversion systems have become a key technology to harvest wind energy worldwide. In permanent magnet synchronous generator-based wind turbine systems, the rotor position is needed for variable speed control and it uses an encoder or a speed sensor. However, these sensors lead to some obstacles, such as additional weight and cost, increased noise, complexity and reliability issues. For these reasons, the development of new sensorless control methods has become critically important for wind turbine generators. This paper aims to develop a new sensorless and adaptive control method for a surface-mounted permanent magnet synchronous generator. The proposed method includes a new model reference adaptive system, which is used to estimate the rotor position and speed as an observer. Adaptive control is implemented in the pulse-width modulated current source converter. In the conventional model reference adaptive system, the proportional-integral controller is used in the adaptation mechanism. Moreover, the proportional-integral controller is generally tuned by the trial and error method, which is tedious and inaccurate. In contrast, the proposed method is based on model predictive control which eliminates the use of speed and position sensors and also improves the performance of model reference adaptive control systems. In this paper, the proposed predictive controller is modelled in MATLAB/SIMULINK and validated experimentally on a 6-kW wind turbine generator. Test results prove the effectiveness of the control strategy in terms of energy efficiency and dynamical adaptation to the wind turbine operational conditions. The experimental results also show that the control method has good dynamic response to parameter variations and external disturbances. Therefore, the developed technique will help increase the uptake of permanent magnet synchronous generators and model predictive control methods in the wind power industry.

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“…Hence, the stability and immunity of the PMSM servo system control algorithm is also worth investigating. In order to improve the anti-disturbance ability of PMSM, Gao et al (2018) used the first-order Euler method to establish a discrete model of a PMSM and, afterward, proposed a single-loop MPC controller that is based on back-electromotive force and I-F control, which combined a current loop and a speed loop. Compared with the single-loop controller, the cascade double-loop control structure realizes the speed control as well as the current output control.…”

Section: Introductionmentioning

confidence: 99%

Speed control of PMSM based on neural network model predictive control

Mao

Tang

2022

Transactions of the Institute of Measurement and Control

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In order to optimize the control performance of permanent magnet synchronous motor (PMSM) servo system, an improved model predictive control (MPC) scheme based on neural network is investigated in this paper. First, the dynamic characteristics of the PMSM are approximated by echo state network (ESN) to predict the future speed. Particle swarm optimization (PSO) is used to train ESN output weights to solve the problem that instability of output weights caused by pseudo-inverse matrix in ESN weight solving algorithm, called PSO-ESN, which enhances the stability and the accuracy of ESN speed prediction. That provides future plant output for control optimization of the predictive control. Furthermore, in order to reduce the computational cost and improve the response performance of the controller, a fast gradient method (GM) is applied to minimize the quadratic performance index and solve the optimal control input sequences. The simulation results under three different working conditions show that the PSO-ESNMPC controller designed in this paper reduces the overshoot by 5.87% and the rise time by 0.036 s compared with the reference controllers and has better robustness under parameter changes and load disturbances.

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A High-efficiency PMSM Sensorless Control Approach Based on MPC Controller

Cited by 8 publications

References 11 publications

Improved Fractional-Order PID Controller of a PMSM-Based Wave Compensation System for Offshore Ship Cranes

Improved Fractional-Order PID Controller of a PMSM-Based Wave Compensation System for Offshore Ship Cranes

New Adaptive Control Strategy for a Wind Turbine Permanent Magnet Synchronous Generator (PMSG)

Speed control of PMSM based on neural network model predictive control

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