In this paper, we propose two adaptive scheduling approaches to support real-time control applications with highly varying computation times. The use of a resource reservation scheduler enables the construction of a dynamic model describing the evolution of the computing delays, which can be incorporated in the system closed loop dynamics. The two approaches differ for the assumptions on the sequence of computation time. In the first approach, we have only an aggregate information (best case and worst case computation time) and design an adaptive scheduler that maintains the delay within the maximum bound compatible with the asymptotic stability of the system. In the second case, we assume a deeper knowledge on the distribution of the computation time and design an adaptive scheduler that ensures second moment stability of the system. The two approaches are evaluated on a case study exposing the different trade-offs between bandwidth and performance.