Adaptive Single Neuron PID Control with Fuzzy and Self-Tuning in Networked Control Systems

Yu, Hai Chen; Shao, Cheng; D, Zhou

doi:10.4028/www.scientific.net/amm.235.152

Cited by 4 publications

(1 citation statement)

References 7 publications

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“…For example, an adaptive fuzzy finite-time coordination controller has been designed for the networked teleoperation system with friction and external disturbances in [88], in which a new finite-time synchronization control scheme has been suggested by using the adaptive fuzzy approximation. By adaptively adjusting the scale factor and learning rate of the neuron with fuzzy rulers, an adaptive single neuron PID control algorithm has been modified for the NCSs in [89]. By means of the integration of an online adaptive Smith predictor and a fuzzy controller, a new control scheme has been investigated for NCSs in [90].…”

Section: Fuzzy Adaptive Controlmentioning

confidence: 99%

Fuzzy-Logic-Based Control, Filtering, and Fault Detection for Networked Systems: A Survey

Luo

Wang

Wei

et al. 2015

Mathematical Problems in Engineering

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This paper is concerned with the overview of the recent progress in fuzzy-logic-based filtering, control, and fault detection problems. First, the network technologies are introduced, the networked control systems are categorized from the aspects of fieldbuses and industrial Ethernets, the necessity of utilizing the fuzzy logic is justified, and the network-induced phenomena are discussed. Then, the fuzzy logic control strategies are reviewed in great detail. Special attention is given to the thorough examination on the latest results for fuzzy PID control, fuzzy adaptive control, and fuzzy tracking control problems. Furthermore, recent advances on the fuzzy-logic-based filtering and fault detection problems are reviewed. Finally, conclusions are given and some possible future research directions are pointed out, for example, topics on two-dimensional networked systems, wireless networked control systems, Quality-of-Service (QoS) of networked systems, and fuzzy access control in open networked systems.

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Section: Fuzzy Adaptive Controlmentioning

confidence: 99%