In this letter, support vector regression (SVR)- and adaptive neuro-fuzzy inference system (ANFIS)-based controllers are implemented for position control of a three-phase permanent magnet brushless DC (PMBLDC) motor. The performance of proposed control schemes is compared with the conventional PI controller for different angular positions of the rotor. The simulation results show the effectiveness of the proposed schemes in terms of rise time \((t_\mathrm{r})\) and steady-state error \((e_\mathrm{ss})\) with ANFIS showing an improvement of 99.2% and SVR showing 90.6% for steady-state error in comparison with the conventional PI approach. The improvement for rise time is 4% and 1.4% by ANFIS and SVR, respectively, in comparison with the conventional PI approach.

在这封信中，实现了基于支持向量回归（SVR）和自适应神经模糊推理系统（ANFIS）的控制器，用于三相永磁无刷直流（PMBLDC）电动机的位置控制。针对转子的不同角度位置，将所提出的控制方案的性能与常规PI控制器进行了比较。仿真结果表明，所提方案在上升时间\（（t_ \ mathrm {r}）\）和稳态误差\（（e_ \ mathrm {ss}）\\）方面均有效，而ANFIS则显示出了改进。与传统的PI方法相比，稳态误差为99.2％，SVR显示为90.6％。与传统的PI方法相比，ANFIS和SVR分别将上升时间提高了4％和1.4％。