Plant-state-based Feedback Scheduling 1
A constant challenge in embedded systems development is represented by computational resource limitations. In fact, economic constraints impose the desired functionalities to be performed with the lowest cost. These limitations call for a more efficient use of the available resources. In this context, integrated control and scheduling methodologies have been proposed in order to allow a more flexible and efficient utilization of the computational resources [ÅRZ 00].
The problem of optimal sampling period selection, subject to schedulability con-straints, was first introduced in [SET 96]. Considering a bubble control system benchmark, the relationship between the control cost (corresponding to a step response) and the sampling periods were approximated using convex exponential functions. Using the Karush–Kuhn–Tucker (KKT) first-order optimality conditions, the analytic expressions of the optimal off-line sampling periods were established. The problem of the joint optimization of control and off-line scheduling has been studied in [REH 04; LIN 02; BEN 06c].
The idea of feedback scheduling was introduced in [EKE 00; LU 02]. First ap-proaches in feedback scheduling considered feedback from resource utilization (for example task execution times) in order to optimize the control performance [EKE 00; CER 02], or to minimize a deadline miss ratio in soft real-time systems [LU 02]. Nat-urally, the on-line adjustment of sampling ...