伪卫星协同编队控制与仿真

Control and Simulation of Collaborative Formation for Pseudolites

为保持4颗编队伪卫星的最佳几何布局,设计了一种综合自适应神经网络编队控制器,利用李亚普诺夫稳定性理论证明了"长机一僚机"方式的两机编队系统的稳定性。以两机编队为单元,根据相对位置和参考坐标系统,采用综合自适应神经网络结构对伪卫星系统进行分布式协同编队控制,使系统快速跟踪指令并保持最佳编队队形。对以无人机为平台的4颗伪卫星编队进行仿真,结果表明僚机能够快速跟随长机飞行并保持最佳编队队形,证明该编队控制器具有良好的稳定性和鲁棒性。

To maintain optimal geometric layout of the four pseudolites, an integrated adaptive neural network controller is designed for the pseudolites formation. The stability of a two-aircraft system based on ＂leader-follo- wer＂ formation is proved by using Lyapunov stability theory. According to the relative position and the refer- ence coordinate system, with two-aircraft as a unit, a set of new distributed collaborative control algorithms is proposed by using integrated adaptive neural network structure to maintain the pseudolites system as the best formation and track instructions fast. The algorithms are applied to the formation control for four airborne pseudolites that use unmanned air vehicles （UAVs） as platforms. The simulation results show that followers can quickly follow the leader and maintain the best formation. It is proved that the formation controller has good sta- bility and robustness.