Cooperative Adaptive Iterative Learning Fault-Tolerant Control Scheme for Multiple Subway Trains

In this article, a cooperative adaptive iterative learning fault-tolerant control (CAILFTC) algorithm with the radial basis function neural network (RBFNN) is proposed for multiple subway trains subject to the time-iteration-dependent actuator faults by using the multiple-point-mass dynamics model....

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Vydané v:	IEEE transactions on cybernetics Ročník 52; číslo 2; s. 1098 - 1111
Hlavní autori:	Liu, Genfeng, Hou, Zhongsheng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.02.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Actuators Adaptive control Adaptive iterative learning control (ILC) Algorithms Convergence cooperative control Fault tolerance Fault tolerant control Headways Iterative learning control Iterative methods Machine learning multiple subway trains multiple-point-mass dynamics model Neural networks Public transportation Radial basis function Radial basis function networks radial basis function neural network (RBFNN) Tracking errors
ISSN:	2168-2267, 2168-2275, 2168-2275
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