Trade-Off Analysis of Real-Time Control Performance and Schedulability*

Authors:
Danbing Seto;John P. Lehoczky;Lui Sha;Kang G. Shin
Affiliations:
Pratt & Whitney, United Technologies Corp., 400 Main Street, MS 163-14 East Hartford, CT 06108;Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213;Department of Computer Science, University of Illinois, 1304 W. Springfield Avenue, Urbana, IL 61801;Real-Time Computing Laboratory, Department of Electrical Engineering and Computer Science, The University of Michigan, Ann Arbor, MI 48109
Venue:
Real-Time Systems
Year:
2001

Citing 3
Cited 4

Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment

Journal of the ACM (JACM)
Task Period Selection and Schedulability in Real-Time Systems

RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Best-effort decision-making for real-time scheduling

Best-effort decision-making for real-time scheduling

Real Time Scheduling Theory: A Historical Perspective

Real-Time Systems
Dynamic Voltage Scaling for Digital Control System Implementation

Real-Time Systems
Fuzzy logic based feedback scheduler for embedded control systems

ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part II
A proposal for on-line reconfiguration based upon a modification of planning scheduler and fuzzy logic control law response

ISSADS'05 Proceedings of the 5th international conference on Advanced Distributed Systems

Quantified Score

Hi-index	0.01

Visualization

Abstract

Most real-time computer-controlled systems are developed in two separate stages: controller design followed by its digital implementation. Computational tasks that implement the control algorithms are usually scheduled by treating their execution times and periods as unchangeable parameters. Task schedulability therefore depends only on the limited computing resources available. On the other hand, controller design is primarily based on the continuous-time dynamics of the physical system being controlled. The set of tasks resulting from this controller design may not be schedulable with the limited computing resources available. Even if the given set of tasks is schedulable, their overall performance may not be optimal in the sense that they do not make a full use of the computing resources. In this paper, we propose an integrated approach to controller design and task scheduling. Specifically, task frequencies (or periods) are allowed to vary within a certain range as long as such changes do not affect critical control functions such as the maintenance of system stability. We present an algorithm that determines the task frequencies such that a prescribed aspect of system performance is optimized subject to satisfaction of computing resource constraints. The tasks are then scheduled with the chosen frequencies. The proposed approach also addresses the issue of choosing controller processors.