Scheduling strategy based on BP neural network and fuzzy feedback in networked control system

For the performance of networked control system is limited to the network resources and compute resources, the scheduling strategy is the key factor. This paper proposed two level schedule strategy: First, the controller and sensor nodes can be configured as event-time hybrid driven mode to improve...

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Bibliographic Details
Published in2009 International Conference on Machine Learning and Cybernetics Vol. 2; pp. 806 - 810
Main Authors Wei-Hua Pan, Pu Han, Li-Jing Zhang, Tian-Kun Wang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2009
Subjects
BP neural network
Communication system control
Computer networks
Event-time driven
Fuzzy control
Fuzzy feedback
Fuzzy neural networks
Fuzzy systems
Information scheduling
Networked control system
Networked control systems
Neural networks
Neurofeedback
Processor scheduling
Scheduling algorithm
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Summary:For the performance of networked control system is limited to the network resources and compute resources, the scheduling strategy is the key factor. This paper proposed two level schedule strategy: First, the controller and sensor nodes can be configured as event-time hybrid driven mode to improve the utilization rate. Then, considering the error and error difference response, a BP neural network and fuzzy feedback scheduler that shares communication net is designed with the bandwidth constraints. Two different scheduling algorithms with stochastic delay are compared with respectively. Finally, the results of simulation highlights that proposed scheduling strategy can optimize the performance of control loop and is more flexible than the other algorithms in uncertain running conditions.
ISBN:9781424437023
1424437024
ISSN:2160-133X
DOI:10.1109/ICMLC.2009.5212460