PWM整流器模型预测控制的研究

发布时间：2018-05-21 06:32

本文选题：PWM整流器 + 电压定向控制　；参考：《中国矿业大学》2017年硕士论文

【摘要】：随着我国现代化进程地不断推进,各种工业设备和家用电器的精密程度也越来越高。为了提高生产效率、延长设备的使用寿命,人们对电能质量提出了更高的要求。然而,不论是在工业领域还是日常生活领域都存在大量的非线性负载,非线性负载产生大量的谐波,导致电网功率因数偏低,对电气设备带来了不利的影响。相比较于二极管等不可控整流器,PWM整流器作为一种“绿色”电能变换装置,不仅能够实现网侧电流正弦化,而且其直流侧电压稳定可控,可以从根源上消除谐波源,从而减少电网损耗,提高电气设备的运行效率。本文基于两电平三相电压源型PWM整流器结构,对PWM整流器的控制策略进行了研究。本文对三相电压源型PWM整流器数学模型进行了详细推导,对其控制策略进行了深入的研究。作为一种比较成熟的控制策略,基于电网电压定向的控制策略可以实现良好的稳态性能,但是其动态性能不够理想,PI参数的设计以及调节比较麻烦。为了提高整流器的动态性能,简化控制器参数设计,本文介绍了模型预测控制策略。单矢量FCS-MPC控制策略简单,动态性能良好,但是其开关频率不固定,等效开关频率低,稳态性能较差;双矢量FCS-MPC稳态性能较单矢量FCS-MPC有较大提高,但是其动态响应较差。FCS-MPC在选取最优矢量时将八个矢量都带入整流器数学模型进行计算,这极大地增加了处理器的负担,不利于系统性能的提升。针对这一问题,本文提出了一种简化算法,该算法不需要计算八个矢量的预测电流,从而减少了处理器的运算时间。不论是单矢量FCS-MPC还是双矢量FCS-MPC,功率管的开关频率均不是恒定的。为了实现功率管开关频率恒定,提高整流器的稳态性能,本文提出了一种定频模型预测控制算法,该算法通过计算得出在下一采样时刻作用的电压矢量,利用SVPWM调制算法将电压矢量转换成相应的开关信号,从而实现定频控制。针对模型预测控制算法易受模型参数失配以及外界干扰影响的缺点,本文将扩张状态观测器与模型预测控制相结合,将参数失配引起的模型误差和外界干扰通过观测器进行观测,将观测的结果进行前馈,实时修改系统的数学模型,从而消除参数失配以及外界干扰的影响,实现预测算法的鲁棒控制。本文对于扩张状态观测器的观测误差进行了分析,分析结果表明:扩张状态观测器观测出的扰动与实际值非常接近,由此可看出采用扩张状态观测器来观测扰动是合适的。为了验证算法的有效性,本文做了相关的仿真和实验,仿真和实验结果均验证了本文所提控制方法的有效性。
[Abstract]:With the development of modernization in our country, the precision of various industrial equipments and household appliances is becoming more and more high. In order to improve the production efficiency and prolong the service life of the equipment, people put forward higher requirements to the power quality. However, there are a large number of nonlinear loads in both the industrial and daily life fields. The nonlinear load produces a large number of harmonics, which leads to the low power factor of the power grid, which has a negative impact on the electrical equipment. Compared with the uncontrollable rectifier such as diode, PWM rectifier, as a kind of "green" power conversion device, can not only realize the sinusoidal current on the grid side, but also the DC side voltage is stable and controllable, which can eliminate the harmonic source from the source. Thus reducing the loss of power grid and improving the operation efficiency of electrical equipment. Based on the structure of two-level three-phase voltage source PWM rectifier, the control strategy of PWM rectifier is studied in this paper. In this paper, the mathematical model of three-phase voltage source PWM rectifier is derived in detail, and its control strategy is deeply studied. As a mature control strategy, the control strategy based on voltage orientation can achieve good steady-state performance, but its dynamic performance is not ideal enough to design and adjust Pi parameters. In order to improve the dynamic performance of rectifier and simplify the design of controller parameters, the model predictive control strategy is introduced in this paper. The control strategy of single vector FCS-MPC is simple, the dynamic performance is good, but its switching frequency is not fixed, the equivalent switching frequency is low, the steady-state performance of double-vector FCS-MPC is poor, and the steady-state performance of double-vector FCS-MPC is better than that of single-vector FCS-MPC. However, the dynamic response of FCS-MPC is poor. FCS-MPC brings eight vectors into the mathematical model of rectifier to calculate when selecting the optimal vector, which greatly increases the processor's burden and is not conducive to the improvement of system performance. To solve this problem, this paper proposes a simplified algorithm, which does not need to calculate the predictive current of eight vectors, thus reducing the computing time of the processor. Whether it is single vector FCS-MPC or double vector FCS-MPC, the switching frequency of power transistor is not constant. In order to keep the switching frequency constant and improve the steady-state performance of the rectifier, a fixed frequency model predictive control algorithm is proposed in this paper. The voltage vector acting at the next sampling time is obtained by the algorithm. The voltage vector is converted into the corresponding switching signal by SVPWM modulation algorithm, and the constant frequency control is realized. In this paper, the extended state observer is combined with the model predictive control to overcome the disadvantage that the model predictive control algorithm is easily affected by the model parameter mismatch and external disturbance. The model error and external disturbance caused by parameter mismatch are observed through the observer, the results of observation are feedforward, and the mathematical model of the system is modified in real time, so as to eliminate the influence of parameter mismatch and external disturbance. The robust control of prediction algorithm is realized. In this paper, the observation error of the extended state observer is analyzed. The results show that the disturbance observed by the extended state observer is very close to the actual value, which shows that it is appropriate to use the extended state observer to observe the disturbance. In order to verify the validity of the algorithm, the simulation and experiment results show that the proposed control method is effective.
【学位授予单位】：中国矿业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM461

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