Dynamic Intelligent Feedback Scheduling in Networked Control Systems

Li, Zuxin

doi:10.1155/2013/584393

Cited by 5 publications

(10 citation statements)

References 18 publications

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“…The output response curves of 3 control loops based on scheduling method in literature (Chen et al, 2013). algorithm based on fuzzy feedback in literature (Chen et al, 2013) and the scheduling method in this paper.…”

Section: Simulationmentioning

confidence: 99%

“…When conflict does not exist in the network, the priority scheduler is dormant and will not affect the normal operation of network. In order to compare the control performance of the system, a variable sampling period scheduling algorithm based on fuzzy feedback was studied (Chen et al, 2013). The input reference signal is a step signal.…”

Section: Simulationmentioning

confidence: 99%

“…The quadratic square Figure 16. The data transmission delay curve of three control loops based on scheduling method in literature (Chen et al, 2013). Figure 17.…”

Section: Simulationmentioning

confidence: 99%

“…The fixed sampling period scheduling algorithm has disadvantages, so many scholars have conducted a lot of research work on the variable sampling period scheduling algorithm. The author determined each loop-sampling period through a two-dimensional fuzzy logic controller (Chen et al, 2013). The input of these fuzzy logic controllers is the network transmission bandwidth and control loop transmission error, but the paper has not provided fuzzy rules on how to determine the loop-sampling period.…”

Section: Introductionmentioning

confidence: 99%

“…The author determined each loop-sampling period through a two-dimensional fuzzy logic controller (Chen et al, 2013). The input of these fuzzy logic controllers is the network transmission bandwidth and control loop transmission error, but the paper has not provided fuzzy rules on how to determine the loop-sampling period.…”

mentioning

confidence: 99%

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Scheduling method for networked control system with resource constraints based on fuzzy feedback priority and variable sampling period

Tian

Wang

et al. 2016

Transactions of the Institute of Measurement and Control

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A scheduling method based on fuzzy feedback priority and variable sampling period for a networked control system with resource constraints is proposed in this paper. Firstly, each control loop weight is adjusted dynamically according to a control loop data transmission error through a quadratic square root mapping function. A different weight is given for each loop. A fuzzy feedback priority scheduling strategy is designed combined with dynamic weight, system output and system output error rate. The priority of each control loop is adjusted dynamically. Then, considering the current network status, the new network utilization is predicted through proportional control. A least-squares support vector machine (LSSVM) algorithm is used for controlled loop packet transmission time prediction. A variable sampling period for each control loop is determined by using a controlled loop dynamic weight, network utilization and data transmission time. Finally, a fuzzy feedback priority scheduler and variable sampling period scheduler are combined. The merits of the two schedulers are utilized to achieve the optimization goal. A simulation experiment is carried out using the True Time toolbox. Simulation results show that the scheduling method can make the network utilization rate converge to the desired value under resource constraints, improve the output response performance of the control loop, reduce the integral absolute error value of the control loop and decrease the data transmission time of the control loop. The networked control system performance is improved and the scheduling method of this paper is effective.

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Section: Simulationmentioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

“…The quadratic square Figure 16. The data transmission delay curve of three control loops based on scheduling method in literature (Chen et al, 2013). Figure 17.…”

Section: Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Scheduling method for networked control system with resource constraints based on fuzzy feedback priority and variable sampling period

Tian

Wang

et al. 2016

Transactions of the Institute of Measurement and Control

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Landscape composition influences colony growth in the tropical asian stingless bees (Tetragonula fuscobalteata)

Wayo,

Leonhardt,

Chuttong

et al. 2023

J Insect Conserv

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Pollination is an important ecosystem service for both crop and wild plants. In recent decades, many pollinators have been experiencing population declines due to land-use changes and intensi ed agriculture. However, effects of anthropogenic landscapes on bee pollinators in the tropics are still little investigated. ObjectivesWe analyzed the effects of landscape composition on the colony weight as well as foraging activity and patterns of the tropical Asian stingless bee species Tetragonala fuscobalteata which is a vital generalist pollinator in Southeast Asia. MethodsTwenty-eight colonies were established and monitored over a year in 19 mixed fruit orchards located along a gradient of human land-use intensity. ResultsOur results revealed that the colonies gained weight and increased their foraging activity over time across diverse landscapes including forest, agricultural, and urbanized areas, indicating that this bee species can well adapt to anthropogenic landscapes. Interestingly, T. fuscobalteata colonies also gained weight rapidly in orchards located in predominately agricultural landscapes with e.g. high proportions of rubber and oil palm plantations as well as in fruit orchards (such as rambutan, durian, coconut, banana). This positive effect was possibly due to mass owering crops providing abundant resources, i.e., pollen and nectar, for a limited time. We also show that T. fuscobalteata foragers could rely on urbanized land (probably ornamental plants and some crops in home gardens and backyards) and wild plants in surrounding forest patches during non-owering periods of crops. ConclusionsOur ndings thus indicate that the combined oral resource availability provided by heterogeneous anthropogenic landscapes, including agricultural elds, urbanized areas and forests, can sustain generalist pollinators.

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Event-triggered robust control and dynamic scheduling co-design for networked control system

Niu

Liang

Yang

2017

2017 14th International Bhurban Conference on Applied Sciences and Technology (IBCAST)

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Dynamic Intelligent Feedback Scheduling in Networked Control Systems

Cited by 5 publications

References 18 publications

Scheduling method for networked control system with resource constraints based on fuzzy feedback priority and variable sampling period

Scheduling method for networked control system with resource constraints based on fuzzy feedback priority and variable sampling period

Landscape composition influences colony growth in the tropical asian stingless bees (Tetragonula fuscobalteata)

Event-triggered robust control and dynamic scheduling co-design for networked control system

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