Description: 基于BP神经网络的电机系统的波形控制
阐述了BP神经网络模型和算法,建立了电流型交——交变频同步电动机的波形控制神经网络BP模型,并将计算结果与仿真结果作了比较。-BP neural network-based motor control system waveform expounded BP neural network models and algorithms of current pay-- Cycloconverter Synchronous Motor waveform control neural network model, results of the computation and simulation results were compared. Platform: |
Size: 60416 |
Author:汪顺和 |
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Description: DSP2407 基于神经网络的交流电机控制源程序,具有PID参数自整定功能。-DSP2407 based on neural network source AC motor control with PID parameter self-tuning function. Platform: |
Size: 5120 |
Author:yuguo |
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Description: 摘要
本文在对永磁同步电动机进行电磁分析设计的基础上,采用MATLABISIMULINK仿真工具对控制系统分别采用PID控制、神经网络控
制的情况进行了仿真分析。-Abstract In this paper, permanent magnet synchronous motor for electromagnetic analysis and design, based on the simulation tool used MATLABISIMULINK on the control system were used PID control, neural network control of a simulation analysis. Platform: |
Size: 2223104 |
Author:王大钊 |
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Description: 直流电机调速系统模糊控制的仿真设计,有比较使用的控制段程序-DC Motor Speed Control System Simulation and Design of fuzzy control, have compared the procedure to control the use of paragraph Platform: |
Size: 1024 |
Author:jonin |
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Description: 该PPT提供了无刷电机无位置控制的新方法...RBF神经网络控制...我们积极在这方面做实验,取得了一定的效果-The PPT provides a brushless motor without position control of the new method ... RBF neural network control ... We are actively conducting experiments in this regard, and achieved some results Platform: |
Size: 95232 |
Author:gexiaozhong |
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Description: 从盲声源信号的独立性出发!提出了一种新的盲声源混合信号分离方法:该方法基于信号联合概率的
分布统计!利用信号联合概率的方向导数熵最小获得最佳的旋转角度!最终实现盲信号分离:与快速独立分
量分析方法及神经网络方法相比!该方法不需要迭代计算:采用新的盲声源信号分离方法对轴承试验台的混
合声音信号进行识别!将电机和滚动轴承的声音分离出来!进而可以准确识别机械的故障-Blind sound source from the independence of the starting signal! Proposed a new mixed-signal blind sound source separation method: This method is based on joint probability distribution of signal statistics! Use of signal joint probability of directional derivative entropy minimum get the best rotation angle ! finally realize blind signal separation: with the fast independent component analysis and neural network methods! This method does not require iterative calculation: the introduction of a new blind signal separation method of sound source on the bearing test bed of mixed sound signals to identify! to motor and rolling bearings separated voice! which can accurately identify the mechanical failure Platform: |
Size: 143360 |
Author:长衫 |
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Description: 伺服电机的神经网络参数自整定程序,利用BP误差反向传播算法改变PID 控制参数以获得优越的控制效果-Servo motor parameters of the neural network self-tuning procedures, the use of error back-propagation algorithm BP to change PID control parameters for superior control Platform: |
Size: 1024 |
Author:阿满 |
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Description: 包含Simulink在控制系统、人工神经网络中的应用-With Simulink in the control system, the application of artificial neural network Platform: |
Size: 373760 |
Author:丁豆 |
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Description: this matlab program uses GRNN neural network tocontrol the speed of Linear induction Motor Drive, both m-file and simulink file are inclu-this is matlab program uses GRNN neural network tocontrol the speed of Linear induction Motor Drive, both m-file and simulink file are includd Platform: |
Size: 38912 |
Author:tarek |
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Description: A VECTOR CONTROLLED INDUCTION MOTOR DRIVE
WITH NEURAL NETWORK BASED SPACE VECTOR PULSE
WIDTH MODULATOR Platform: |
Size: 157696 |
Author:q |
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Description: Abstract-This paper introduces the new concept of Artificial
Neural Networks (ANNs) in estimating speed and
controlling the separately excited DC motor. The neural
control scheme consists of two parts. One is the neural
estimator, which is used to estimate the motor speed. The
other is the neural controller, which is used to generate a
control signal for a converter. These two networks are
trained by Levenberg-Marquardt back propagation
algorithm. Standard three layer feed forward neural
network with sigmoid activation functions in the input and
hidden layers and purelin in the output layer is used.
Simulation results are presented to demonstrate the
effectiveness and advantage of the control system of DC
motor with ANNs in comparison with the conventional
control scheme. Platform: |
Size: 490496 |
Author:amidi |
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Description: This paper describes a Model Reference Adaptive
System (MRAS) based scheme using a multilayer
Recurrent Neural Network (RNN) for online speed
estimation of sensorless vector controlled inductmon
motor drive.
Platform: |
Size: 11264 |
Author:chinni |
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