永磁同步电机伺服控制系统研究与设计

发布时间：2018-09-08 18:10

【摘要】：永磁无刷电机既有永磁同步电动机体积小、损耗低、效率高的特性，又具有造价低、驱控方便、运行可靠的自身优势，因此越来越广泛地被应用于伺服控制、航空器材、工业设备和汽车等行业。但是，目前多数永磁无刷电机控制系统存在着诸如控制策略陈旧、转矩脉动大、无位置传感器控制可靠性低等一系列问题，限制了其在高性能场合的应用和推广。因此，针对这些问题进行改善和优化一直是控制领域的研究热点，研制开发具备良好伺服特性的永磁无刷电机控制系统，具有长远的实践及理论价值。本文就永磁无刷电机的构造与运行原理、转矩脉动抑制技术、智能控制等方面进行深入研究，并完成了无刷电机驱控系统的设计和实现。针对永磁无刷电机时变性强、非线性度高的特点，对永磁无刷电机的基本结构、组成特点和工作原理进行探索、建立其数学模型，分析无刷电机的驱动电路、控制策略及调速方式，完成了永磁无刷电机理论层面的研究。针对无刷电机运转时存在的转矩脉动特别是换相转矩脉动问题，首先对比分析5种不同PWM控制模式对无刷电机换相转矩脉动的影响，，定量比较得出PWM_ON方式的优越性；接下来深入分析无刷电机换相期间的线圈电流波动和换相转矩脉动的产生过程，揭示出换相转矩脉动产生的本质原因；在此基础上提出一种减少换相转矩脉动的“12步换相”控制策略，并和传统“6步换相”策略进行对比仿真。实验证明，该方法可以有效降低换相转矩脉动，增强电机运行平滑性。针对永磁无刷电机的伺服控制性能问题，研究PID控制的工作原理，对传统PID控制器在无刷电机控制上所显示的不足进行分析和归纳；提出一种基于PID神经元网络的智能控制策略，介绍了神经元PID的特点和优势，并对其控制系统进行了算法设计和实现；在永磁无刷电机闭环控制设计时运用神经元PID控制器，利用神经元的自学习功能，可以对系统参数进行实时训练和修改；分别对基于传统PID和神经元PID控制器完成的无刷电机控制系统进行仿真。测试证明神经元PID控制器可以提高无刷电机的响应速度和工作特性。相关理论分析和算法设计完成之后，对永磁无刷电机控制系统软硬件进行开发和设计。硬件方面，以NUC130RC1CN处理器为核心，对控制器外围电路及各个功能模块进行了设计和说明，在设计中分别集成了有霍尔和无霍尔两种闭环控制方式、总线电流和相电流两种电流采集方式、RS-485和CAN两种通信方式，以满足不同的应用需求；软件方面，基于硬件电路对软件程序进行了开发和实现，并对关键模块的实现流程进行阐述；可靠性方面，对软硬件实现过程中所采用的EMC及程序代码可靠性设计技术进行了介绍。
[Abstract]:Permanent magnet brushless motor has the advantages of small size, low loss, high efficiency, low cost, convenient drive and reliable operation, so it is widely used in servo control, aviation equipment, etc. Industries such as industrial equipment and automobiles. However, most permanent magnet brushless motor control systems have a series of problems such as outmoded control strategy, large torque ripple, low reliability of sensorless control, and so on, which limit its application and popularization in high performance situations. Therefore, to improve and optimize these problems has always been the research hotspot in the field of control. The development of permanent magnet brushless motor control system with good servo characteristics has long-term practical and theoretical value. In this paper, the construction and operation principle of permanent magnet brushless motor (PMSM), torque ripple suppression technology and intelligent control are studied deeply, and the design and implementation of brushless motor drive control system are completed. In view of the characteristics of permanent magnet brushless motor with strong time-varying and high nonlinearity, the basic structure, composition and working principle of permanent magnet brushless motor are explored, its mathematical model is established, and the driving circuit of brushless motor is analyzed. Control strategy and speed regulation method, completed the permanent magnet brushless motor theoretical level research. Aiming at the torque ripple, especially the commutation torque ripple of brushless motor, the influence of five different PWM control modes on commutation torque ripple of brushless motor is analyzed, and the superiority of PWM_ON mode is obtained by quantitative comparison. Then, the generation process of coil current fluctuation and commutation torque ripple during commutation of brushless motor is analyzed, and the essential reason of commutation torque ripple is revealed. On this basis, a "12 step commutation" control strategy to reduce commutation torque ripple is proposed and compared with the traditional "6 step commutation" strategy. Experimental results show that this method can effectively reduce commutation torque ripple and enhance the smoothness of motor operation. Aiming at the servo control performance of permanent magnet brushless motor, the working principle of PID control is studied, and the deficiency of traditional PID controller in brushless motor control is analyzed and summarized. This paper presents an intelligent control strategy based on PID neural network, introduces the characteristics and advantages of neuron PID, designs and implements its control system, and applies neuron PID controller to the closed-loop control design of permanent magnet brushless motor. The system parameters can be trained and modified in real time by using the self-learning function of neurons, and the brushless motor control system based on traditional PID and neuron PID controller is simulated respectively. The test results show that the neural PID controller can improve the response speed and performance of the brushless motor. After theoretical analysis and algorithm design, the hardware and software of permanent magnet brushless motor control system are developed and designed. In terms of hardware, the peripheral circuits and function modules of the controller are designed and explained with NUC130RC1CN processor as the core. In the design, two closed-loop control methods, Hall and Hall free, are integrated respectively. Bus current and phase current two kinds of current acquisition methods RS-485 and CAN to meet the different needs of application software based on the hardware circuit to develop and implement the software program. In the aspect of reliability, the EMC and program code reliability design technology used in the process of software and hardware implementation are introduced.
【学位授予单位】：宁波大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM341

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