Formation reconfiguration of multiple unmanned aerial vehicles (UAVs) is a challenging problem. Mathematically, this problem is an optimal control problem subject to continuous state inequality constraints and terminal state equality constraints. The first challenge is that there are an infinite number of constraints to be satisfied for the continuous state inequality constraints, which makes the problem extremely difficult to be solved. The second challenge is that the control and state are usually both been discretized. This will result in noncontinuous control input. In addition, the discretized system may not always accurately approximate the original system. In this paper, a hybrid offline optimization scheme is proposed to tackle these problems. Unlike the existing methods, the state variables are not required to be discretized and continuous control inputs can be obtained. In addition, the continuous state inequality constraints are tackled without increasing the total number of constraints. Simulation results show that the proposed hybrid optimization method outperforms the state-of-the-art method - the hybrid particle swarm optimization and genetic algorithm (HPSOGA).

中文翻译：

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一种多无人机编队重构的混合离线优化方法

多架无人机（UAV）的编队重构是一个具有挑战性的问题。在数学上，这个问题是一个受连续状态不等式约束和终端状态等式约束的最优控制问题。第一个挑战是连续状态不等式约束需要满足的约束数量是无限的，这使得该问题极难解决。第二个挑战是控制和状态通常都是离散化的。这将导致不连续的控制输入。此外，离散化系统可能并不总是准确地逼近原始系统。在本文中，提出了一种混合离线优化方案来解决这些问题。不同于现有的方法，状态变量不需要离散化，可以获得连续的控制输入。此外，在不增加约束总数的情况下解决了连续状态不等式约束。仿真结果表明，所提出的混合优化方法优于最先进的方法——混合粒子群优化和遗传算法（HPSOGA）。