scholarly journals Permanent-Magnet Synchronous Motor Sensorless Control Using Proportional-Integral Linear Observer with Virtual Variables: A Comparative Study with a Sliding Mode Observer

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 877 ◽  
Author(s):  
Baochao Wang ◽  
Yangrui Wang ◽  
Liguo Feng ◽  
Shanlin Jiang ◽  
Qian Wang ◽  
...  

Quick convergence, simple implementation, and accurate estimation are essential features of realizing permanent-magnet synchronous motor (PMSM) position estimation for sensorless control using microcontrollers. A linear observer is often designed on real plant variables and is more sensitive to parameter uncertainty/variations. Thus, conventionally, a sliding mode observer (SMO)-based technique is widely used for its simplicity and convergence ability against parameter uncertainty. Although SMO has been improved for switching chattering and phase delay, it provides purely proportional gain, which leads to steady-state error and chattering in observation results. Different from conventional linear observer using real plant variables or SMO with proportional gain, a simple proportional-integral linear observer (PILO) using virtual variables is proposed in this paper. This paper also provides a comparative study with SMO. By introducing virtual variables without physical meaning, the PILO is able to simplify observer relations, get smaller phase shifts, adapt mismatched parameters, and obtain a fixed phase-shift relation. The PILO is not only simple, but also improves the estimation precision by solving the controversy between chattering and phase-delay, steady-state error. Moreover, the PILO is less sensitive to parameters mismatching. Simulation and experimental results indicate the merits of the PILO technique.

Author(s):  
Peikun Zhu ◽  
Yong Chen ◽  
Meng Li

Aiming at the parameter uncertainty and load torque disturbance of permanent magnet synchronous motor system, a terminal sliding mode control algorithm for permanent magnet synchronous motor based on the reaching law is proposed. First, a sliding mode control algorithm for sliding mode reaching law is proposed, which can dynamically adapt to the changes in system state. Second, a sliding mode disturbance observer is designed to estimate the lumped disturbance in real time and to compensate the controller for disturbance. On this basis, an online identification method based on disturbance observer for viscous friction coefficient and moment of inertia is used to reduce the influence of parameter uncertainty on the control system. Simulation and experimental results show the effectiveness of the method.


2021 ◽  
Vol 12 (2) ◽  
pp. 74
Author(s):  
Wengen Gao ◽  
Gang Zhang ◽  
Mengxun Hang ◽  
Sirui Cheng ◽  
Pengfei Li

This paper analyzes the problems and the reasons of high frequency chattering, phase delay, unmanageable with low-speed rotation in the traditional SMO control strategy of the sensor-less control strategy of a permanent magnet synchronous motor based on the traditional sliding mode observer. Aiming at the shortcomings of the above-mentioned traditional SMO control strategy, an improved SMO control strategy is presented by replacing the signum function in the traditional synovial observer with the sigmoid function to reduce the high frequency chattering of the system. Meanwhile, the proposed improved SMO control strategy introduces an adaptive filter to eliminate harmonics and chattering, and adaptively compensates the estimated back-EMF value to reduce the estimation error caused by the phase delay. The improved SMO strategy was tested through Matlab/Simulink simulation and real experiments respectively. The results verified that the improved SMO strategy can significantly reduce chattering and phase delay and achieve good control performance at low speeds, as well as maintain good performance at full speed.


Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2786 ◽  
Author(s):  
Yichang Zhong ◽  
Shoudao Huang ◽  
Derong Luo

The permanent magnet synchronous motor (PMSM) with dual-rotating rotors is a typical nonlinear multi-variable coupled system. It is sensitive to load disturbances and the change of interior parameters. The traditional proportional-integral (PI) controller is widely used in the speed control of a motor because of its simplicity; however, it cannot meet the requirements needed for high performance. In addition, when the loads of both of the rotors change, it is difficult to ensure that the system runs stably. With an aim to mitigate these problems, a method called master-slave motor control is proposed to guarantee the stability of the motor system in all cases. And then, a speed controller is designed to eliminate the influence of uncertain terms. The proposed control strategy is implemented both in simulations and in experiments. Through the analysis and comparison of the proportional-integral (PI) controller and the sliding-mode controller, the effectiveness of the proposed control strategy is validated.


2011 ◽  
Vol 130-134 ◽  
pp. 300-303
Author(s):  
Ping Zhang ◽  
Zheng Qiang Song

This paper presents a comparative study of two popular Evolutionary Algorithms (EA): GeneticAlgorithms (GA) andParticle Swarm Optimization (PSO) for optimal tuning of Proportional Integral (PI) speed controller in Permanent Magnet Synchronous Motor (PMSM) drives.Comparisons between the results obtained by GA method and those by improved PSO method are made. The experimental results show that the PSO method can locate the optimal or near optimal parameter space and achieve a higher quality solution than the GA method.


Sign in / Sign up

Export Citation Format

Share Document