Formation of heterogeneous multi-agent systems under min-weighted persistent graph

Abstract

In this paper, we develop a simple and efficient formation control framework for heterogeneous multi-agent systems under min-weighted persistent graph. As the ability of each agent may be different, the architecture of agents is considered to be heterogeneous. To reduce the communication complexity of keeping connectivity for agents, a topology optimisation scheme is proposed, which is based on min-weighted persistent graph. According to the topology of agents, a directed acyclic graph (DAG) is constructed to reflect the signal flow relation of agents, and then the corresponding formation control protocol is designed by using the transfer function model. Apply the proposed method, it is shown that the communication complexity of multi-agent systems is decreased, and the connection safety is improved. Based on signal flow graph analysis and Mason's rule, the convergence conditions are provided to show the agents can keep a formation. Finally, several simulations are worked out to illustrate the effectiveness of our theoretical results. X. (2017) 'Formation of heterogeneous multi-agent systems under min-weighted persistent graph', Int. the University Office of Research Management. His current research interests include cyber-physical systems, multiagent systems, wireless networking and applications in smart city and smart factory, and underwater sensor networks. Y. Sun et al.The main challenge in formation control is to design a decentralised control law by depending on local information interaction. Thus, fundamental questions about what local interaction rules are and how they work, are raised. To interpret these questions, some local interaction schemes were proposed, such as game-based method (Hu et al., 2015;Semsar-Kazerooni and Khorasani, 2009), graph-based method (Aguilar and Gharesifard, 2015;Olfati-Saber, 2006), etc. In these references, 'neighbour rule' was widely applied in the topology communication between agents, wherein each agent was required to communicate with its neighbours in the topology interaction graph to keep the connectivity of multi-agent systems. Analysing the action of 'neighbour rule' in formation control, we find that some interactions between agents can be removed during the formation process. Accordingly, the energy consumption with respect to communication between agents is increased. To reduce the communication complexity, Ding et al. (2010) schematically represented the neighbouring relationship of networked agents as a directed acyclic graph (DAG), wherein the cycles in topology interaction graph were deleted. On the other hand, some scholars studied the rigid and persistent configurations to decrease the communication complexity (Zhang et al., 2015). Yan et al. (2015) and Chen et al. (2015) studied optimally rigid formation, wherein the least communication number was required. Although the number of communication links is the least, these rigid graphs are not unique. If the edges of the graphs are weighted by the required communication energy, how to find the min-weighted graph...