Dynamic scheduling of real-time control systems

Abstract

In this thesis, a systematic way to evaluate the task on-line urgency change in real-time is developed. Based on this on-line task urgency, a dynamic scheduling algorithm for on-line adjustment of task periods is proposed. An aperiodic sampling method is employed in the dynamic scheduling algorithm to improve the efficiency of CPU usage. Task periods are regarded as variables dependent on the on-line performance index change rate of the tasks and system scheduling constraints. Simulation results are presented to compare our on-line dynamic scheduling algorithm with the traditional designed scheduling algorithm. The simulation results show that with on-line dynamic scheduling the system performance is improved.