【摘要】 研究交流电机系统特性,针对常规模糊推理系统自学习能力不强,用支持向量机与模糊系统结合,提出了一种支持向量机-模糊推理系统,由支持向量机实现模糊推理系统的自学习。设计一种基于自适应混沌优化算法的支持向量机-模糊推理自学习控制器,并将其应用于无速度传感器感应电机矢量控制系统的速度控制。控制系统采用定转子自适应磁通观测器估计磁通,用转速动态估计器来估算转子转速。仿真结果表明,控制方法响应速度快,鲁棒性强,稳定性好,是一种有效的控制方法。更多还原

【Abstract】 Aiming to the poor self-learning ability of conventional fuzzy inference system(FIS),the support vector machines was hybrid with the fuzzy inference system,and a self-learning controller based on support vector machines-fuzzy inference system(SVM-FIS) was proposed in this paper.The self-learning capability of fuzzy inference system was realized using support vector machines(SVM).A SVM-FIS self-learning controller based on self-adaptive chaotic optimization algorithm was designed,and it is applied to the speed-sensorless induction motor vector control system,in which the stator-rotor adaptive flux observer is used to estimate flux,and the speed dynamitic estimator is used to estimate rotor speed.Simulation results show that this control method is effective with rapid response speed,strong robustness and good stability.更多还原