论文标题
BNB-DAQP：一种用于嵌入式应用的混合智能QP求解器
BnB-DAQP: A Mixed-Integer QP Solver for Embedded Applications
论文作者
论文摘要
我们提出了一个适用于嵌入式应用程序的混合二次编程（QP）求解器，例如混合模型预测性控制（MPC）。该求解器基于分支结合的方法，并使用最近提出的双活动设定求解器来求解所得的QP松弛。此外，我们调整对分支和结合树的搜索，以适用于有限的硬件上的嵌入式应用程序；例如，我们展示了只有两个整数可以表示分支和结合树中的节点。通过成功运行具有有限的内存和计算能力的MCU接触力的倒置的倒置摆的MPC，可以显示求解器的嵌入性。
We propose a mixed-integer quadratic programming (QP) solver that is suitable for use in embedded applications, for example, hybrid model predictive control (MPC). The solver is based on the branch-and-bound method, and uses a recently proposed dual active-set solver for solving the resulting QP relaxations. Moreover, we tailor the search of the branch-and-bound tree to be suitable for embedded applications on limited hardware; we show, for example, how a node in the branch-and-bound tree can be represented by only two integers. The embeddability of the solver is shown by successfully running MPC of an inverted pendulum on a cart with contact forces on an MCU with limited memory and computing power.
