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A Convex Optimization Approach to Feedback Scheduling

Mohamed El Mongi Ben Gaïd 1, 2 Daniel Simon 1 Olivier Sename 3
1 NECS [2007-2015] - Networked Controlled Systems
GIPSA-DA - Département Automatique, Inria Grenoble - Rhône-Alpes
3 GIPSA-SLR - GIPSA - Systèmes linéaires et robustesse
GIPSA-DA - Département Automatique
Abstract : Adaptive tasks scheduling via feedback is an effective solution for the optimization of closed-loop control performance under computing power limitation, as in the computing nodes of embedded networked control systems. The problem of the feedback scheduling of a set of Linear-Quadratic controllers, based on both plant-state and resource utilization measurements is considered. The proposed feedback scheduler acts on tasks periods in order to minimize a quadratic cost functional over an infinite horizon, for the overall system, and to achieve a desired processor utilization. Based on Karush-Kuhn-Tucker conditions, it is shown that if Riccati matrix coefficients may be approximated using parabolic functions of the sampling frequency, the expressions of optimal sampling frequencies may be computed analytically. Examples where these approximations hold are presented and the approach is illustrated on a simulation example.
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Contributor : Mohamed El Mongi Ben Gaid <>
Submitted on : Sunday, May 11, 2008 - 7:00:06 AM
Last modification on : Wednesday, October 7, 2020 - 11:40:09 AM
Long-term archiving on: : Friday, May 28, 2010 - 5:49:23 PM


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  • HAL Id : inria-00276005, version 1


Mohamed El Mongi Ben Gaïd, Daniel Simon, Olivier Sename. A Convex Optimization Approach to Feedback Scheduling. 16th Mediterranean Conference on Control and Automation (MED'08), Mediterranean Control Association/IEEE, Jun 2008, Ajaccio, France. ⟨inria-00276005⟩



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