【作者】 雷华；

【导师】 王明渝；

【作者基本信息】 重庆大学 ， 电气工程， 2003， 硕士

【摘要】 采用矢量控制技术可解决传统交流调速的难题，使交流电机可以按直流电机的控制规律来进行控制；而无速度传感器的矢量控制技术由于可以省去速度传感器，而使相应的交流调速系统变得简便、廉价和可靠，所以成为当前研究的热点，论文正是在这一背景下展开对无速度传感器矢量控制技术的研究。首先，论文介绍了无速度传感器矢量控制技术的基本理论，并且在比较了已提出的诸多速度估计方案后，采用神经网络速度估计方案，主要是因为国内在这方面的研究还处于起步阶段，而神经网络控制相对于传统的控制方法而言又具有很多优点（诸如自学习、自适应性、超强的非线性逼近和泛化能力，不依赖于系统模型的精确性等），所以很有必要将神经网络控制的优点应用到具体的控制系统中。其次，论文介绍了神经网络的一些基本理论，根据神经网络模式识别原理，应用了三种基于神经网络的速度估计方案，建立了相应的神经网络速度估计模型，确定了该模型的结构和学习算法（BP算法）。针对BP算法所存在的问题，根据实际的应用，论文采用了动量法、学习率自适应调整法和权值衰减法来改进传统的BP算法，并结合具体的神经网络模型推导出相应的软件实现算法。再次，论文根据无速度传感器矢量控制技术的基本理论，建立了相应的系统仿真模型，并通过Matlab Simulink仿真对其工作性能进行了验证。同时，对所采用的速度估计方案进行了仿真分析，证明了神经网络速度估计模型相对于传统的速度估计模型而言，估计精度高，并且对参数的变化和铁耗的影响具有很强的鲁棒性。最后，论文采用具体的多组实验数据，再次检验了神经网络速度估计模型的估计性能，其结果再次表明神经网络速度估计模型的估计精度很高，估计转速能很好地跟踪实际转速。而且，论文⑦ 通过采用某种状态下训练的神经网络和另一状态的实验数据来进行速度估计，证明了神经网络模型具有很强的容错性、范化功能以及对非线性系统的逼近能力。更多还原

【Abstract】 Vector control can solve the problems of the tranditional induction motor drives and makes induction motor easy to control like DC motor, while speed sensorless vector control can eliminate the speed sensors which makes the relative induction motor drives simple, economical and reliable. For this reason, the speed sensorless vector control is becoming the attractive researching project, and under this circumstance, the thesis begins to undertake the study of speed sensorless vector control.Firstly, the thesis introduces the theories of speed sensorless vector control, then selects the neural network (NN) speed estimation scheme after comparing the presented schemes before. The reason is that compared with other traditional control methods, NN control has many advantages, such as self-study, self-adaptability, generalization ability and capability of approaching nonlinear system with arbitrary precision. Besides, in our country, such a research is just being undertaken, so it is necessary to study NN control and apply it to the real systems.Secondly, some NN theories are introduced and three NN speed estimation schemes based on NN mode identification principle are adopted. Also, the relative NN model is established and its structure and study arithmetic is confirmed. Thirdly, a simulation model based on the speed sensorless vector control principle is established, and its good operation performance is proved by simulation. Also, the presented NN speed estimation schemes are discussed and the simulation results show that compared to the traditional schemes, the NN schemes have good speed estimation precision. Moreover, they are robust to the variation of motor parameters and not sensitive to the effect of iron loss.Finally, the good performance of NN speed estimation model is proved once more with experimental data. Besides, by using the NN trained under one condition and the experimental data acquired under another condition to estimate speed, the thesis proves that the NN model can approach the real nonlinear system with arbitrary precision and has the function of fault- tolerance and generalization.更多还原