Optimal tracking cooperative control for multi-agent systems with periodic sampling via robust model predictive control approach

摘要

This paper addresses the optimized tracking cooperative control problem for multi-agent systems with periodic sampling and directed communication topology via robust model predictive control approach. The proposed optimized tracking cooperative control strategy relaxes the assumptions in existing works that the control gain and the local input must be continuous and the states information exchange has no recourse constraints. With the conditions of the optimized consensus and the communication cost being satisfied, the tracking cooperative control law with bounded parameters is developed based on the periodic samples. It shows that if the sampling condition is satisfied, the multi-agent systems will reach the optimized consensus. Simulation results are provided to verify the proposed approach.