Quality-of-Control Management in Overloaded Real-Time Systems
IEEE Transactions on Computers
FC-ORB: A robust distributed real-time embedded middleware with end-to-end utilization control
Journal of Systems and Software
DEUCON: Decentralized End-to-End Utilization Control for Distributed Real-Time Systems
IEEE Transactions on Parallel and Distributed Systems
Distributed algorithms for partially clairvoyant dispatchers
Cluster Computing
On the design and implementation of a shared memory dispatcher for partially clairvoyant schedulers
International Journal of Parallel Programming
Networked control system: survey and directions
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
INtERCEDE: An algorithmic approach to networked control system design
Journal of Network and Computer Applications
An enhanced dynamic voltage scaling scheme for energy-efficient embedded real-time control systems
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part IV
Current design practice and needs in selected industrial sectors
Embedded Systems Design
Embedded Systems Design
Embedded Systems Design
Hi-index | 0.00 |
Closed-loop control systems are dynamic systems subject to perturbations. One of the main concerns of the control is to design controllers to correct or limit the deviation that transient perturbations cause in the controlled system response. The smaller and shorter the deviation, the better the achieved performance. However, such controllers have been traditionally implemented using fixed timing constraints (periods and deadlines). This precludes controllers to execute dynamically, accordingly to the system dynamics, which may lead to sub-optimal implementations: although higher execution rates may be preferable when reacting to perturbations in order to minimize the response deviations, they imply wastage of resources when the system is in equilibrium.In this paper we argue and demonstrate that the responsibility of maximizing the performance of closed-loop systems relies on both the controller designer and the scheduler. We show that the dynamic optimization of the quality of the controlled system response calls for (a) flexible control task timing constraints that deliver effective control performance; flexible constraints allow us to achieve faster reaction by adaptively choosing the controller sampling rate and completion time upon transient perturbations, (b) a Quality-of-Control (QoC) metric; it associates with each control task timing a quantitative value expressing control performance (in terms of the closed-loop system error), and (c) new scheduling approaches; their goal is to quickly react to perturbations by dynamically scheduling tasks based on the chosen control task execution parameters to maximize the QoC. This combination offers the possibility of taking scheduling decisions based on the control information for each control task invocation, rather than using fixed timing constraints with constant periods and deadlines.