Adaptive neural quantized control for fractional-order full-state constrained non-strict feedback systems subject to input fault and nonlinearity

In this work, an adaptive neural network (NN)-based quantized fault-tolerant controller (FTC) has been designed for incommensurate fractional-order (FO) nonlinear systems (NSs) in the non-strict feedback form subject to independent asymmetric time-varying full-state constraints, input quantization,...

Celý popis

Podrobná bibliografie

Vydáno v:	Chaos, solitons and fractals Ročník 166; s. 112977
Hlavní autoři:	Pishro, Aboozar, Shahrokhi, Mohammad, Mohit, Mohammaderfan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.01.2023
Témata:	Fault-tolerant quantized controller Fractional-order non-strict systems Incommensurate derivatives Neural network Quantized input State constraints Quantized input Fault-tolerant quantized controller Fractional-order non-strict systems Neural network Incommensurate derivatives State constraints
ISSN:	0960-0779, 1873-2887
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!