Formation control for multiquadrotor aircraft: Connectivity preserving and collision avoidance

Abstract

Summary In this article, we investigate the formation control problem of multiquadrotor aircraft system subject to connectivity preservation and collision avoidance. First, based on the backstepping design method, a novel formation control algorithm is developed to enable multiquadrotor aircraft to move along the desired trajectory while becoming the predefined formation pattern. Meanwhile, the connectivity of the communication network is maintained and the collision among multiquadrotor is avoided. Second, for each quadrotor's desired attitude obtained by the formation controller, an improved finite‐time attitude tracking law is designed to guarantee that the desired attitude can be tracked by the real attitude in a fast finite time. Finally, a numerical example is given to demonstrate the effectiveness of the proposed algorithms.

Target enclosing control of multiple unmanned aerial vehicles based on crowd entropy

“…文 献 [10]考虑了合围目标运动速度信息未知的情况, 提 出了一种基于事件触发动态面控制的目标合围控制 方法. 文献 [11]考虑了部分个体不具备感知能力的情 况, 基于反演设计方法设计了一种集群势函数实现 了四旋翼无人机的目标合围控制. 文献 [12]针对有向 通信拓扑下具有多个领导者的高阶多智能体系统的 包围控制问题, 提出了一种仅基于邻域智能体相对 输出测量的分布式包围控制协议, 消除了一些现有 方法中普遍使用的多智能体系统中跟随者的观测器 必须与其邻居个体共享信息的假设.…”

Distributed time-varying formation tracking of multi-quadrotor systems with partial aperiodic sampled data

“…Lemma 1 [25] For the attitude error dynamics (27) with control law (28), the desired attitude is achieved in finite time, i.e. ∥η i − η di ∥ → 0 if α 3 and α 4 are chosen as 0 < α 3 < 1 and α 4 = 2α 3 /(1 + α 3 ).…”

“…In [24], a formation tracking algorithm for time-varying formation has been presented. A formation tracking control scheme has been proposed in [25] where the position and attitude dynamics are considered as two subsystems and two controllers are designed separately to control both subsystems. However, the closed-loop stability analysis was not provided.…”

UAV swarm containment control inspired by spatial interaction mechanism of wolf-pack foraging

“…尽管合围控制问题在多智能体协调控制领域已 得到广泛研究, 但任务环境的不确定性、合围过程中 可能出现的失效和中断等未知因素仍旧是其亟待解 决的主要难点. 传统合围控制方法按照不同约束条 件可分为基于连通拓扑的一致性控制 [7][8][9][10][11][12] 与人工势 场 [13][14][15][16][17] 两类方法. 一致性控制方法主要基于固定或 连通拓扑结构设计控制律, 以求使集群系统能够在 有限时间内收敛于相对目标实时位置的期望合围队 形, 常用于存在模型和环境不确定性的任务环境.…”