Dynamic Target Enclosing Control Scheme for Multi-Agent Systems via a Signed Graph-Based Approach

Li, Weihao; Qin, Kaiyu; Shi, Mengji; Shao, Jingliang

doi:10.1109/jas.2023.123234

Cited by 14 publications

(2 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the phenomena of divergence are equally common in nature, for instance, the split of a school of fish when encountering an obstacle [4] and the division of an ant colony on their way to food sources [5,6]. In a similar way, when many practical multi-agent systems [7][8][9], especially UAV groups [10][11][12], perform complex behavior, such as coverage [13], formation [14], enclosing [15], surrounding [16] and containment [17], their states exhibit divergence in order to fulfill civil and military tasks related to searching and exploring by space expansion rather than convergence. Relevant studies show that the bipartition of a UAV network is an effective use of divergence behavior.…”

Section: Introductionmentioning

confidence: 99%

Robust Cooperative Control of UAV Swarms for Dual-Camp Divergent Tracking of a Heterogeneous Target

Jiang

Qin

et al. 2023

Drones

Self Cite

View full text Add to dashboard Cite

Agents are used to exhibit swarm intelligence in the sense of convergence, while divergence is equivalently common in nature and useful in complex applications for multi-UAV systems. This paper proposes a robust target-tracking control algorithm, where UAV swarms are partitioned by a signed graph to perform opposite movements along or against the trajectory of the target. Uncertainties take place in both the fractional-order model of the target and the double-integrator dynamics of the UAVs. To tackle the challenge induced by the bipartite behavior and unknown components in the multi-UAV systems, the article comes up with a backstepping cascade controller and a new method for uncertainty estimation-compensation via a combined approach based on a neural network (NN) and an Uncertainty and Disturbance Estimator (UDE). Steered by the controller, UAVs in a structurally balanced network will display symmetry of their paths, pursuing or away from the target with respect to the origin. Theoretical derivation and numerical simulations have evidenced that the tracking errors converge to zero. Compared with the traditional NN method to solve such problems, this method is proposed for the first time, which can effectively improve the precision of cooperative target tracking and reduce the chattering phenomena of the controller.

show abstract

Section: Introductionmentioning

confidence: 99%

Robust Cooperative Control of UAV Swarms for Dual-Camp Divergent Tracking of a Heterogeneous Target

Jiang

Qin

et al. 2023

Drones

Self Cite

View full text Add to dashboard Cite

show abstract

“…There has been extensive research to address the problem of target capture [4], for example, the strategy based on reinforcement learning [5,6], game theory methods [7][8][9], planar reach-avoid games [10,11], consensus based [12], leader-follower [13], and others [14]. Another distinctive method is the parallel optimization method based on time minimization [15].…”

Section: Introductionmentioning

confidence: 99%

Omni-Directional Capture for Multi-Drone Based on 3D-Voronoi Tessellation

Cao

Chen

Gao

et al. 2023

Drones

View full text Add to dashboard Cite

This paper addresses the multi-drone formation capture in three-dimensional (3D) environments. The omni-directional minimum volume (ODMV) 3D-Voronoi diagram algorithm is proposed for the first time to achieve the two goals of (1) forming and keeping a capture and (2) planning the control action within its safe, collision region for each drone. First, we extend the traditional 2D Voronoi diagram to the 3D environment and use the non-overlapping spatial division property of 3D Voronoi diagram to inherently avoid the collision between drones. Second, we make improvements to the problem of capture angle in our minimum area strategy and propose an omni-directional minimum volume strategy to accomplish the effective capture of a target by constraining the capture angle. Finally, the wolf pack algorithm (WPA) with variable step size is introduced to provide a movement strategy for multi-drone formations. Thus, the proposed ODMV can also achieve dynamic target and multi target capture in environments with obstacles. The Optitrack motion capture system and Crazyflie drones are used to conduct the multi-drone capture experiment. Both simulation and experimental results are included to demonstrated the effectiveness of the proposed ODMV method.

show abstract

Event-triggered prescribed performance control of multi-spacecraft formation with communication and computation constraints

Liu

Shi

et al. 2023

Aerospace Science and Technology

View full text Add to dashboard Cite

Dynamic Target Enclosing Control Scheme for Multi-Agent Systems via a Signed Graph-Based Approach

Cited by 14 publications

References 17 publications

Robust Cooperative Control of UAV Swarms for Dual-Camp Divergent Tracking of a Heterogeneous Target

Robust Cooperative Control of UAV Swarms for Dual-Camp Divergent Tracking of a Heterogeneous Target

Omni-Directional Capture for Multi-Drone Based on 3D-Voronoi Tessellation

Event-triggered prescribed performance control of multi-spacecraft formation with communication and computation constraints

Contact Info

Product

Resources

About