Consensus of heterogeneous multi-agent system in switching network using model predictive control

This work shows an approach to achieve output consensus among heterogeneous agents in a multi-agent environment where each agent is an uncertain linear system subject to input and state constraints. The communication among agents is described by a time-varying directed graph with bounded communication delays. The approach relies on achieving consensus among the references of the agents and that each agent has a Model Predictive Controller (MPC) that tracks piecewise constant references asymptotically. A notable contribution is the characterization of the trackable references for every agents. This set of trackable references for each agent is used to ensure output consensus for all agents. Since consensus is imposed on the references, the recursive feasibility condition of MPC can be easily satisfied. The choice of the control parametrization also allows for a large domain of applicability. Examples are provided to illustrate the advantages of the approach.