This paper focuses on the distributed model predictive control for
multi-agent systems subject to packet loss and actuator saturation. The
multi-agent systems, which can be decoupled into several subsystems,
have a coupled global cost function. By decoupling the global cost
function, the distributed model predictive control for multi-agent
systems is approximately cast into centralized model predictive control
for each agent with a cost function including the states of the
neighboring agents. The exchange of states between adjacent agents
realized by communication network may subject to packet loss which is
assumed to obey a Bernoulli distribution with probability being known.
Actuator saturation is also considered and dealt with by the Nth-step
set invariance approach. To ensure the multi-agent systems is
asymptotically stable, a compatibility condition is provided. The
problem of controller design for agent is converted into a Linear matrix
inequality optimization problem involving compatibility constraint.
Furthermore, a control algorithm is obtained to ensure the asymptotic
stability of the global closed-loop system as well as the recursive
feasibility of the optimization problem. Finally according to a
simulation example, it is concluded that the presented method is
effective.