CN110266228A - 基于bp神经网络的表面式永磁同步电机模型预测控制方法 - Google Patents
基于bp神经网络的表面式永磁同步电机模型预测控制方法 Download PDFInfo
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- CN110266228A CN110266228A CN201910603590.XA CN201910603590A CN110266228A CN 110266228 A CN110266228 A CN 110266228A CN 201910603590 A CN201910603590 A CN 201910603590A CN 110266228 A CN110266228 A CN 110266228A
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- 230000005291 magnetic effect Effects 0.000 title claims abstract description 58
- 238000004422 calculation algorithm Methods 0.000 title claims abstract description 56
- 230000001360 synchronised effect Effects 0.000 title claims abstract description 30
- 239000013598 vector Substances 0.000 claims description 71
- 239000010410 layer Substances 0.000 claims description 68
- 230000006870 function Effects 0.000 claims description 32
- 238000012549 training Methods 0.000 claims description 32
- 238000000034 method Methods 0.000 claims description 24
- 230000008859 change Effects 0.000 claims description 16
- 238000003062 neural network model Methods 0.000 claims description 8
- 230000004907 flux Effects 0.000 claims description 7
- 210000002569 neuron Anatomy 0.000 claims description 7
- 230000005284 excitation Effects 0.000 claims description 6
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- 238000006243 chemical reaction Methods 0.000 claims description 3
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
- H02P21/0014—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control using neural networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
- H02P21/24—Vector control not involving the use of rotor position or rotor speed sensors
- H02P21/28—Stator flux based control
- H02P21/30—Direct torque control [DTC] or field acceleration method [FAM]
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Cited By (8)
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---|---|---|---|---|
CN110715405A (zh) * | 2019-09-29 | 2020-01-21 | 华中科技大学 | 一种基于bp神经网络拟合模型的空调器制冷量检测方法 |
CN111241749A (zh) * | 2020-01-13 | 2020-06-05 | 广西师范大学 | 一种基于储备池计算的永磁同步电动机混沌预测方法 |
CN111612242A (zh) * | 2020-05-15 | 2020-09-01 | 北京天工智造科技有限公司 | 一种基于lstm深度学习模型的电机状态参数预测方法 |
CN111769770A (zh) * | 2020-01-17 | 2020-10-13 | 华中科技大学 | 直线感应电机多步长有限集模型预测控制方法及*** |
CN111915054A (zh) * | 2020-06-08 | 2020-11-10 | 唐山钢铁集团有限责任公司 | 一种基于离线神经网络的重卷延伸率自适应优化方法 |
CN112691783A (zh) * | 2020-12-09 | 2021-04-23 | 华润电力技术研究院有限公司 | 一种煤粉锅炉制粉***调控方法、装置、设备及存储介质 |
CN116027672A (zh) * | 2023-03-28 | 2023-04-28 | 山东大学 | 基于神经网络的模型预测控制方法 |
WO2023124921A1 (zh) * | 2021-12-31 | 2023-07-06 | 深圳先进技术研究院 | 永磁同步电机的转矩估测方法、装置、设备及存储介质 |
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EP2546979A1 (en) * | 2011-07-15 | 2013-01-16 | ABB Research Ltd. | Method for controlling harmonics and resonances in an inverter |
CN103259479A (zh) * | 2013-05-28 | 2013-08-21 | 江苏大学 | 一种永磁同步电机神经网络左逆状态观测方法 |
CN107968613A (zh) * | 2017-11-20 | 2018-04-27 | 无锡开放大学 | 一种基于递归模糊神经网络的永磁同步电机转速控制器 |
CN109327178A (zh) * | 2018-10-29 | 2019-02-12 | 江苏大学 | 一种开关磁阻电机多步预测控制器构造方法 |
CN109873581A (zh) * | 2017-12-04 | 2019-06-11 | 北京自动化控制设备研究所 | 一种基于神经网络的永磁同步电机直接速度控制方法 |
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2019
- 2019-07-05 CN CN201910603590.XA patent/CN110266228B/zh active Active
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EP2546979A1 (en) * | 2011-07-15 | 2013-01-16 | ABB Research Ltd. | Method for controlling harmonics and resonances in an inverter |
CN103259479A (zh) * | 2013-05-28 | 2013-08-21 | 江苏大学 | 一种永磁同步电机神经网络左逆状态观测方法 |
CN107968613A (zh) * | 2017-11-20 | 2018-04-27 | 无锡开放大学 | 一种基于递归模糊神经网络的永磁同步电机转速控制器 |
CN109873581A (zh) * | 2017-12-04 | 2019-06-11 | 北京自动化控制设备研究所 | 一种基于神经网络的永磁同步电机直接速度控制方法 |
CN109327178A (zh) * | 2018-10-29 | 2019-02-12 | 江苏大学 | 一种开关磁阻电机多步预测控制器构造方法 |
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BEN GUO ET AL.: "NN-based model predictive direct speed control of PMSM drive systems", 《2014 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS》 * |
李孟秋 等: "基于BP神经网络的开关磁阻电机直接转矩控制***及实现", 《电力***及其自动化学报》 * |
Cited By (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110715405A (zh) * | 2019-09-29 | 2020-01-21 | 华中科技大学 | 一种基于bp神经网络拟合模型的空调器制冷量检测方法 |
CN111241749A (zh) * | 2020-01-13 | 2020-06-05 | 广西师范大学 | 一种基于储备池计算的永磁同步电动机混沌预测方法 |
CN111241749B (zh) * | 2020-01-13 | 2023-04-07 | 广西师范大学 | 一种基于储备池计算的永磁同步电动机混沌预测方法 |
CN111769770A (zh) * | 2020-01-17 | 2020-10-13 | 华中科技大学 | 直线感应电机多步长有限集模型预测控制方法及*** |
CN111769770B (zh) * | 2020-01-17 | 2022-03-18 | 华中科技大学 | 直线感应电机多步长有限集模型预测控制方法及*** |
CN111612242A (zh) * | 2020-05-15 | 2020-09-01 | 北京天工智造科技有限公司 | 一种基于lstm深度学习模型的电机状态参数预测方法 |
CN111915054A (zh) * | 2020-06-08 | 2020-11-10 | 唐山钢铁集团有限责任公司 | 一种基于离线神经网络的重卷延伸率自适应优化方法 |
CN112691783A (zh) * | 2020-12-09 | 2021-04-23 | 华润电力技术研究院有限公司 | 一种煤粉锅炉制粉***调控方法、装置、设备及存储介质 |
WO2023124921A1 (zh) * | 2021-12-31 | 2023-07-06 | 深圳先进技术研究院 | 永磁同步电机的转矩估测方法、装置、设备及存储介质 |
CN116027672A (zh) * | 2023-03-28 | 2023-04-28 | 山东大学 | 基于神经网络的模型预测控制方法 |
CN116027672B (zh) * | 2023-03-28 | 2023-06-09 | 山东大学 | 基于神经网络的模型预测控制方法 |
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