Fast online model predictive control of IPMSM using parallel computing on FPGA
Fast online model predictive control of IPMSM using parallel computing on FPGA
复制标题
使用 FPGA 上并行计算的 IPMSM 快速在线模型预测控制
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
J. Bocker
中科院分区：
文献类型：
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作者：
Michael Leuer;J. Bocker
模型预测控制（MPC）提供了各种优势相比，传统的控制方法。MPC的问题是高计算成本和相关联的长控制周期时间。这使得MPC的使用对于具有小时间常数的过程没有吸引力，如在用于电动车辆的具有内部磁体的永磁同步电机（IPMSM）中。本文针对具有固有输出限制的非线性系统提出了一种模型预测控制方法。这种方法为在线MPC提供了实时能力，即使是时间常数在毫秒范围内的进程。这通过如FPGA（现场可编程门阵列）所提供的并行计算的可能性而变得可行。在下文中，提出了这种实时MPC方法的功能原理，并且通过用于汽车应用的IPMSM控制的仿真结果来验证该功能。
Model predictive control (MPC) offers a variety of advantages compared to conventional control methods. The problem with MPCs is the high computational cost and the associated long control cycle time. This makes the use of MPCs unattractive for processes with small time constants, as in permanent magnet synchronous motors with interior magnets (IPMSM) for electric vehicles. In this paper a model predictive control method for nonlinear systems with inherent output limitation is presented. This approach offers real-time capability for online MPCs even for processes with time constants in the millisecond range. This becomes feasible by the possibility of parallel computation, as provided by a FPGA (Field Programmable Gate Array). In the following, the functional principle of this real-time MPC approach is presented and the functionality is verified by simulation results of an IPMSM control for automotive applications.