Computer-controlled systems (3rd ed.)
Computer-controlled systems (3rd ed.)
QoS Negotiation in Real-Time Systems and Its Application to Automated Flight Control
IEEE Transactions on Computers
Fuzzy Control
Trade-Off Analysis of Real-Time Control Performance and Schedulability*
Real-Time Systems
Feedback–Feedforward Scheduling of Control Tasks
Real-Time Systems
RTAS '97 Proceedings of the 3rd IEEE Real-Time Technology and Applications Symposium (RTAS '97)
Feedback Scheduling of Model Predictive Controllers
RTAS '02 Proceedings of the Eighth IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'02)
Analysis of a Reservation-Based Feedback Scheduler
RTSS '02 Proceedings of the 23rd IEEE Real-Time Systems Symposium
Managing Quality-of-Control Performance Under Overload Conditions
ECRTS '04 Proceedings of the 16th Euromicro Conference on Real-Time Systems
Real Time Scheduling Theory: A Historical Perspective
Real-Time Systems
Neural network based feedback scheduler for networked control system with flexible workload
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Flexible quality-of-control management in embedded systems using fuzzy feedback scheduling
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Integrated computation, communication and control: towards next revolution in information technology
CIT'04 Proceedings of the 7th international conference on Intelligent Information Technology
Neural network based feedback scheduling of multitasking control systems
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Anytime iterative optimal control using fuzzy feedback scheduler
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
NN-Based iterative learning control under resource constraints: a feedback scheduling approach
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
A hybrid neural-genetic approach for reconfigurable scheduling of networked control system
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
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The case where multiple control tasks share one embedded CPU is considered. For various reasons, both execution times of these tasks and CPU workload are uncertain and imprecise. To attack this issue, a fuzzy logic based feedback scheduling approach is suggested. The sampling periods of control tasks are periodically adjusted with respect to uncertain resource availability. A simple period rescaling algorithm is employed, and the available CPU resource is dynamically allocated in an intelligent fashion. Thanks to the inherent capacity of fuzzy logic to formalize control algorithms that can tolerate imprecision and uncertainty, the proposed approach provides runtime flexibility to quality of control (QoC) management. Preliminary simulations highlight the benefits of the fuzzy logic based feedback scheduler.