| CMAC神经网络在变磁阻电动机转矩控制中的应用 |
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| 引用本文： | 王晓升.CMAC神经网络在变磁阻电动机转矩控制中的应用[J].浙江国际海运职业技术学院学报,2007,3(1):5-7,12. |
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| 作者姓名： | 王晓升 |
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| 作者单位： | 浙江国际海运职业技术学院 浙江舟山316021 |
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| 摘 要： | 结合变磁阻电动机的工作特点,提出了应用小脑模型神经网络控制SRM转矩的控制器结构和改进的学习算法。该算法是在原算法的基础上增加了一个与可变相角有关的约束函数。仿真结果表明:该系统不但收敛速度没有降低,而且经过训练能够产生理想的电流曲线,在抑制电机转矩脉动和提高有效功率方面具有显著效果。
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| 关 键 词： | 小脑模型神经网络 学习算法 变磁阻电动机 转矩控制 |
| 文章编号： | L019（2007）01-0005-03 |
Applications of CMAC Neural Networks on Torque Controlling of Switched Reluctance Motors |
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| WANG Xiao-sheng.Applications of CMAC Neural Networks on Torque Controlling of Switched Reluctance Motors[J].ZheJiang International Maritime College,2007,3(1):5-7,12. |
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| Authors: | WANG Xiao-sheng |
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| Institution: | Zhejiang International Maritime College, Zhoushan 316021, China |
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| Abstract: | Combining characteristics of switched reluctance motors(SRM),this paper presents a controller architecture and learning algorithm for controlling SRM's torque using cerebellar model articulation controller(CMAC) neural network.The algorithm is increased a constrained function over the rotor angle based on original algorithm.The results of simulation show that the system can not reduce the convergence speed,but it can generate optimal current profiles by training,and has good results on constraining torque pulse and improving effective power. |
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| Keywords: | CMAC learning algorithm switched reluctance motor(SRM) torque control |
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