Dynamic Scheduling of Receding Horizon Controllers with Application to Multiple Unmanned Hovercraft Systems

This paper develops a new algorithm for dynamic scheduling of multiple receding horizon control systems that accounts for bounded model uncertainty and bounded sensor noise. A cost function appropriate for control of multiple vehicle systems is proposed and an upper bound on the cost as a function of the execution horizon is developed. The upper bound is optimized to obtain an optimal schedule subject to the computational constraints. The algorithm is further improved using less conservative upper bounds. The new approach is illustrated through simulation of a two radio controlled hovercraft system.