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A Hybrid Offline Optimization Method for Reconfiguration of Multi-UAV Formations

机译:一种混合离线优化方法,用于重新配置多UV形成

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摘要

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 article, 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.
机译:多种无人驾驶飞行器(无人机)的形成重新配置是一个具有挑战性的问题。在数学上,这个问题是经过连续状态不等式约束和终端状态平等约束的最佳控制问题。第一个挑战是对于连续的状态不等式约束,有一个无限数量的约束,这使得问题极难解决。第二个挑战是,控制和状态通常都被离散化。这将导致非连续控制输入。此外,离散系统可能并不总是准确地近似原始系统。在本文中,提出了一种混合离线优化方案来解决这些问题。与现有方法不同,状态变量不需要离散化,并且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,应解决连续状态不等式约束。仿真结果表明,拟议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。

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