Asignación dinámica de recursos en sistemas de control de tiempo real

Most traditional resource management techniques for real-time systems with multiple control loops are based on "open-loop" strategies that statically allocate a constant CPU share to each control task, independent of the plant dynamics of each control loop. This provides average control performance with minimal overhead but in general fails to provide the best performance possible within the available resources. We show that by using dynamic resource allocation for control tasks, overall control performance can be significantly improved. We present an optimal resource allocation policy that maximizes control performance within the available resources. We provide experimental results on a real-time system that show the benefits of the proposed policies and corroborate the presented theoretical results.