Model Predictive Formation Control Using Branch-and-Bound Compatible With Collision Avoidance Problems
Model Predictive Formation Control Using Branch-and-Bound Compatible With Collision Avoidance Problems
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DOI：
10.1109/tro.2013.2262751
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发表时间：
2013-10
影响因子：
7.8
通讯作者：
H. Fukushima;K. Kon;F. Matsuno
中科院分区：
文献类型：
--
作者：
H. Fukushima;K. Kon;F. Matsuno
提出了一种考虑避碰和速度限制的多车辆编队模型预测控制（MPC）方法。本文的第一部分构造了一个编队控制律，使用反馈线性化与MPC，以减少最优控制问题的混合整数二次规划问题的一组单轮。第二部分构造了一个新的基于分支定界（B& B）的避碰算法。数值算例和实验表明，该方法大大减少了计算时间.
This paper presents a model predictive control (MPC) approach for multivehicle formation taking into account collision avoidance and velocity limitation with reduced computational burden. The first part of the paper constructs a formation control law using feedback linearization with MPC in order to reduce the optimal control problem to a mixed-integer quadratic programming problem for a group of unicycles. The second part constructs a new branch-and-bound (B& B) -based algorithm for collision-avoidance problems. Numerical examples and experiments show that the proposed method significantly reduces computation time.