Event-triggered control of multi-agent systems: pinning control, cloud coordination, and sensor coverage

A multi-agent system is composed of interconnected subsystems, or agents. In control of multi-agent systems, the aim is to obtain a coordinated behavior of the overall system through local interactions among the agents. Communication among the agents often occurs over a wireless medium with finite capacity. In this thesis, we investigate multiagent control systems where inter-agent communication is modelled by discrete events triggered by state conditions. In the first part, we consider event-triggered pinning control for a network of agents with nonlinear dynamics and time-varying topologies. Pinning control is a strategy to steer the behavior of a multi-agent system in a desired manner by controlling only a small fraction of the agents. We express the controllability of the network in terms of an average value of the network connectivity over time, and we show that all the agents can be driven to a desired reference trajectory. In the second part, we propose a control algorithm for multi-agent systems where inter-agent communication is substituted with a shared remote repository hosted on a cloud. Communication between each agent and the cloud is modelled as a sequence of events scheduled recursively by the agent. We quantify the connectivity of the network and we show that it is possible to synchronize the multi-agent system to the same state trajectory, while guaranteeing that two consecutive cloud accesses by the same agent are separated by a finite time interval. In the third part, we propose a family of distributed algorithms for coverage and inspection tasks for a network of mobile sensors with asymmetric footprints. We develop an abstract model of the environment under inspection and define a measure of the coverage attained by the sensor network. We show that the sensor network attains nondecreasing coverage, and we characterize the equilibrium configurations. The results presented in the thesis are corroborated by simulations or experiments.