This thesis develops a new algorithm for the dynamic scheduling of multiple receding horizon control (RHC) systems running on a single processor. The subsystems are coupled and the formulation is adapted for decentralized RHC. The proposed formulation accounts for bounded model uncertainty, sensor noise, and computational delay. 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, which is adapted from Rate Monotonic Scheduling. To consider the computation delay effect, a retarded actuation method based on prediction of the state variables at the next sampling time is employed. The presented scheduling approach first developed for uncoupled systems and extended to the coupled systems, later. Its application is illustrated through control of a three radio controlled hovercraft system and formation control of a four radio controlled hovercraft system.