Mansouri Mohamed, Bey Mohamed, Hassaine Said, Larbi Mhamed, Allaoui Tayeb, Denai Mouloud
Laboratory of Energy Engineering and Computer Engineering, IBN Khaldoun University, Tiaret, Algeria.
School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield, UK.
ISA Trans. 2022 Oct;129(Pt B):230-242. doi: 10.1016/j.isatra.2022.02.004. Epub 2022 Feb 10.
This paper presents an optimal control scheme for a Permanent Magnet Synchronous Generator (PMSG) coupled to a wind turbine operating without a position sensor. This sensorless scheme includes two observers: The first observer uses the flux to estimate the speed. However, an increase in the temperature or a degradation of the permanent magnet characteristics will result in a demagnetization of the machine causing a drop in the flux. The second observer is therefore used to estimate these changes in the flux from the speed and guaranties the stability of the system. This structure leads to a better exchange of information between the two observers, eliminates the problem of encoder and compensates for the demagnetization problem. To improve the precision of the speed estimator, the gain of the non-linear observer is optimized using Genetic Algorithm (GA) and the speed is obtained from a modified Phase Locked Loop (PLL) method using an optimized Sliding Mode Controller (SMC). Furthermore, to enhance the convergence speed of this observer scheme and improve the performance of the system a Fast Super Twisting Sliding Mode Control (FSTSMC) is introduced to reinforce the SMC strategy. A series of simulations are presented to show the effectiveness and robustness of proposed observer scheme.
本文提出了一种用于与无位置传感器运行的风力涡轮机耦合的永磁同步发电机（PMSG）的最优控制方案。这种无传感器方案包括两个观测器：第一个观测器利用磁链来估计转速。然而，温度升高或永磁体特性退化会导致电机退磁，从而使磁链下降。因此，第二个观测器用于根据转速估计磁链的这些变化，并保证系统的稳定性。这种结构实现了两个观测器之间更好的信息交换，消除了编码器问题，并补偿了退磁问题。为提高转速估计器的精度，使用遗传算法（GA）优化非线性观测器的增益，并通过使用优化滑模控制器（SMC）的改进锁相环（PLL）方法获得转速。此外，为提高该观测器方案的收敛速度并改善系统性能，引入了快速超扭曲滑模控制（FSTSMC）来强化SMC策略。给出了一系列仿真结果，以证明所提出观测器方案的有效性和鲁棒性。
