基于快速矢量选择的永磁同步电机模型预测控制

Model Predictive Control of Permanent Magnet Synchronous Motors Based on Fast Vector Selection

有限状态集模型预测控制(FCS-MPC)由于概念简单,易于处理系统约束以及具有优秀的多变量控制能力等优点,近年来在电力电子与电力传动领域的应用吸引了学术界和工业界的广泛关注。基于最小化目标函数的原则,传统FCS-MPC通过枚举法来选择最优电压矢量。由于枚举法需要对所有基本电压矢量作用下的系统动态行为进行预测,因此算法的计算量较大,严重限制了FCS-MPC的实用性。针对这些问题,提出一种改进的模型预测控制算法。通过深入分析矢量选择过程,改进的模型预测控制算法只需一次预测即可选出最优电压矢量,因而显著地降低了算法的复杂度和计算量。在两电平永磁电机实验台上的仿真和实验结果表明所提出的改进模型预测控制算法在较宽的速度范围内均具有良好的控制性能。

In the area of power electronics and motor drives, finite control set model predictive control （FCS-MPC） has attracted increasing attention from both academic and industrial communities, due to its simple concept, easy incorporation of constraints and good multivariable control ability. Based on the principle of cost function minimization, conventional FCS-MPC selects the optimal voltage vector by evaluating all the feasible ones. It is computational intensive and impractical for this method to predict future behaviors of the system under all voltage vectors. Thus, an improved scheme is proposed in this paper. By analyzing the process for vector selection in detail, the proposed method only requires one prediction to select the optimal vector. Hence, the control complexity and computational burden are significantly reduced. Simulation and experimental tests were carried out on a two-level inverter-fed PMSM drive. The results prove that the proposed method exhibits excellent dynamic and steady state performance over a wide speed range.