无差拍优化T型三电平APF模型预测电流控制

为实现T型三电平有源电力滤波器(APF)的高性能电流跟踪控制及其鲁棒性,提出了一种无差拍优化有限集模型预测控制(FCS-MPC)算法,并设计了滤波电感在线观测器。首先,为降低滚动优化过程的运算量,提出了一种基于谐波电流无差拍预测的电压矢量控制集简化方法,减少了每个控制周期内迭代计算的次数。然后,为降低电感参数失配对FCS-MPC算法性能的影响,设计了一种电感观测器完成参数的在线修正。最后,通过仿真对所提算法完成验证。仿真结果表明,所提算法不仅保持了传统FCS-MPC优越的动静态响应性能,同时显著减少了数字实现的运算量,提升了参数失配时控制系统的鲁棒性。

Model predictive current control algorithm with deadbeat optimization for T-type three-level APF

In order to realize the high-performance current tracking control and robustness of T-type three-level active power filter (APF), a no-beat optimization model predictive current control (FCS-MPC) algorithm is proposed and designed. Filter inductor online observer. Firstly, in order to reduce the computational complexity of the rolling optimization process, a simplified method of voltage vector control set based on harmonic current deadbeat prediction is proposed, which reduces the number of iterative calculations in each control cycle. Then, in order to reduce the influence of the inductance parameter mismatch on the performance of the FCS-MPC algorithm, an in-line correction of the parameters of the inductive observer is designed. Finally, the proposed algorithm is verified by simulation. The simulation results show that the proposed algorithm not only maintains the superior dynamic and static response performance of the traditional FCS-MPC, but also significantly reduces the computational complexity of the digital implementation and improves the robustness of the control system when the parameters are mismatched.