Dynamic scheduling of decentralized receding horizon controllers on concurrent processors for the cooperative control of unmanned systems

This paper develops a new algorithm for the dynamic scheduling of multiple receding horizon controllers running on concurrent processors. The proposed formulation accounts for bounded model uncertainty, sensor noise and communication delay. A cost function appropriate for control of multiple vehicle systems on multiple processors is proposed and an upper bound on the cost as a function of the execution horizon and communication period is developed. While the formulation is adapted for decentralized RHC, the coupling between different systems is modeled in a general case. The upper bound is optimized to obtain the execution horizon and communication period of all subsystems subject to the computation and communication constraints. The new approach is illustrated through formation control of four radio controlled hovercraft system running on four computers.