Scaled Consensus of Descriptor Multi-agent Systems

Multi-agent systems have been studied from different perspectives. In this paper, the problem of scaled consensus is considered for descriptor multi-agent systems. In fact, each agent is considered as a descriptor system. This is significant due to the fact that descriptor systems describe a larger group of systems. Furthermore, an algorithm is proposed to drive the agents to different consensus points, which is denoted as scaled consensus. This can also have very important applications in areas such as multi-robot systems where each robot needs to perform a different task. Moreover, in contrast with the works in the literature on scaled consensus, higher order systems are allowed in this paper. Also, as practical systems may suffer from time delay, these systems under a constant delay are considered. Finally, numerical examples are provided to further demonstrate the effectiveness of the proposed algorithms.