论文标题
在分支和结合方法中量身定制的预脉技术，用于快速混合组合最佳控制应用
Tailored Presolve Techniques in Branch-and-Bound Method for Fast Mixed-Integer Optimal Control Applications
论文作者
论文摘要
混合模型预测控制（MI-MPC）可以是建模混合控制系统的强大工具。如果有线性季度目标与线性或分段线性系统动力学和不平等约束结合使用，则需要在每个采样时间步骤中求解混合组合二次程序（MIQP）。本文介绍了一系列块 - 板块预处理技术，以有效地删除决策变量，并删除或拧紧不等式约束，该约束量身定制为混合组的最佳控制问题（MIOCP）。此外，我们描述了一种基于迭代性预溶液算法的新型启发式方法，以计算可行但可能是次优的MIQP解决方案。我们为提出的BB-ASIPM求解器的C代码实现提供了基准测试结果，包括使用拟议的量身定制的PRESOLVE技术和基于主动设置的内部点方法（ASIPM）的分支机构和结合方法（B＆B）方法，与多个最先进的MIQP Solvers相比，在具有易于避免的动作计划的案例研究中，相比之下。最后，我们使用第二个具有软接触的稳定稳定案例研究了DSPACE Scalexio实时嵌入式硬件的BB-ASIPM求解器的计算性能。
Mixed-integer model predictive control (MI-MPC) can be a powerful tool for modeling hybrid control systems. In case of a linear-quadratic objective in combination with linear or piecewise-linear system dynamics and inequality constraints, MI-MPC needs to solve a mixed-integer quadratic program (MIQP) at each sampling time step. This paper presents a collection of block-sparse presolve techniques to efficiently remove decision variables, and to remove or tighten inequality constraints, tailored to mixed-integer optimal control problems (MIOCP). In addition, we describe a novel heuristic approach based on an iterative presolve algorithm to compute a feasible but possibly suboptimal MIQP solution. We present benchmarking results for a C code implementation of the proposed BB-ASIPM solver, including a branch-and-bound (B&B) method with the proposed tailored presolve techniques and an active-set based interior point method (ASIPM), compared against multiple state-of-the-art MIQP solvers on a case study of motion planning with obstacle avoidance constraints. Finally, we demonstrate the computational performance of the BB-ASIPM solver on the dSPACE Scalexio real-time embedded hardware using a second case study of stabilization for an underactuated cart-pole with soft contacts.
