Circle formation control for multi-agent systems with a leader

Consensus of Multiagent System in the Sense of Curvature and Torsion

“…Notice that, in the above results, consensus refers to the fact that the state of each node converges to a same value, or the errors among all agents are limited for the target tracking system. In [14,15], the consensus results show that all trajectories of nodes converge to a curve. In [17], the tracking errors among all trajectories are limited in the permitted range.…”

“…For the past decade, consensus problem of MAS has attracted much attention due to its presence in formation, environmental monitoring, and unmanned aerial vehicles control [9]. Therefore, many results on consensus problems of MAS have been obtained (see, e.g., consensus of the first order MAS [10][11][12][13][14][15][16][17][18][19]; consensus of the second order MAS [20,21]; consensus of the fraction order MAS [22]; and the consensus of the scale free networks [23]).…”

“…Generally, most of us believe that, without considering the curvature function and the torsion function, under the traditional average consensus protocols, the connected networks can achieve the average consensus (see, e.g., [14][15][16][17][18][19][20][21], and the references therein). However, under the traditional consensus protocols, all trajectories of agents converge to a curve with zero distance or converge to a line if we apply the protocol to the tangent, normal, and binormal vectors of each agent directly without considering the curvature function and 2 Mathematical Problems in Engineering the torsion function, and the results are not what we expected sometimes.…”

UAV Formation Shape Control via Decentralized Markov Decision Processes

“…UAV swarm formation and information passing for data fusion within the swarm requires control and optimization strategies that can be implemented in near real-time. Many centralized control [4][5][6][7][8] strategies exist, albeit suffer from exponential computational complexities. To address this challenge, we develop decentralized control and study data fusion methods using a decision theoretic framework called decentralized Markov decision process (Dec-MDP).…”

“…They used figure of eight as reference trajectory; their results show that the UAVs were able to avoid collision with obstacles and among themselves. Several recent papers describe formation control of different geometric shapes, e.g., multi-agent circular shape with a leader [6]. The authors of [6] propose centralized formation control, which is not suitable for swarm control when the number of UAVs in the swarm is large.…”