轉矩脈動是開關磁阻電動機較為突出的缺點,出于電機設計和控制的目的,常需要實時在線測量電機的動態轉矩,采用轉矩
傳感器的方法既復雜、昂貴,在高速下又不準確。利用一種新型變結構模糊神經網絡對開關磁阻電動機轉矩特性進行學習,之后把它用于動態轉矩的實時在線測量。仿真與試驗結果表明此方法能夠快速、準確的測量開關磁阻電機動態轉矩。
關鍵詞　開關磁阻電動機　轉矩脈動　測量　模糊神經網絡
Abstract 　Switched reluctance motor (SRM) produces excessive vibration and torque ripple in low speed area1So the realtime and online measurement of SRM’s torque is required for cont rol and design purpose1However ,the measure2 ment method which using torque t ransducer is complex ,expensive and inaccurate1This paper uses a novel Fuzzy2neu2
ral networks(FNN) to approximate the nonlinear torque characteristics of SRMs as a function of position and current , and then the FNN is applied to online measurement of SRM’s torque1The simulation and experiment result s illust rate the validity of the proposed method1
Key words 　Switched reluctance motor 　Torque ripple 　Measurement 　Fuzzy2neural network