Coordinated control for networked multi-agent systems

Abstract

Coordination in networked multi-agent systems attracts significant interest in the realm of engineering. Typical examples include formations of unmanned aerial vehicles, automated highway systems, and sensor networks. One common feature for these systems is that coordinated behaviors are exhibited by interactions among agents where information exchange and manipulation are necessary. In this work, three relevant issues are investigated in detail: uniform strategy for multi-agent formation control, fast-converging consensus protocols, and packet-based state estimation over communication networks. Formation control of multi-agent systems involves harmony among local controller design, interaction topology analysis, and objective agreement among networked agents. We propose a novel control strategy so that each agent responds to neighbors' behaviors as well as acts towards the global goal. Using the tools from signal flow graphs and algebraic graph theory, we show that this new strategy eases the design of local controllers. Robustness against the link failure and scalable disturbance resistance are also discussed based on small-gain theory. Consensus protocols over communication networks are used to achieve agreement among agents. One important issue is the convergence speed. We propose multi-hop relay protocols for fast consensus seeking. Without physically changing the topology of the communication network, this type of distributed protocol increases the algebraic connectivity by employing multi-hop paths in the network. We also investigate the convergence behaviors of consensus protocols with communication delays. Efficiently estimating the states of other agents over communication links is also discussed in this work. When information flows in the network, packet-based data is normally not retransmitted in order to satisfy real-time requirements. Thus, packet drops and random delays are inevitable. We introduce multiple description source codes to manipulate the data before transmission. Using modified algebraic Riccati equations, we show that multiple description codes improve the performance of Kalman filters over a large set of packet-dropping scenarios. This problem is also generalized to the case where observation data has an independent and identical static distribution over a finite set of observation noise. Moreover, Kalman filtering with bursty packet drops is also discussed based on the two-state Markov chain model.