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Event-triggered Model Predictive Control Applied to Formation Control for Multiple UAVs

The paper proposes an event-triggered model predictive control (MPC) scheme for formation control of multiple unmanned aerial vehicles (UAVs). A distributed MPC framework is designed in which each UAV only shares the information with its neighbors, and the obtained local finite-horizon optimal control problem (FHOCP) can be solved by swarm intelligent optimization algorithm. An event-triggered mechanism is proposed to reduce the computation burden for the distributed MPC scheme, which takes into consideration of the predictive state errors. Further, numerical simulations show that the proposed event-triggered MPC is more computationally efficient to achieve formation control of multiple UAVs in comparison with the tradition distributed MPC scheme.