Adaptive neural output feedback control for uncertain robot manipulators with input saturation

DOI10.1155/2017/7413642zbMath1373.93179OpenAlexW2743575205MaRDI QIDQ1674960

ChengJiang Yu, Rong Mei

Publication date: 26 October 2017

Published in: Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/7413642

zbMATH Keywords

input saturationLyapunov analysisdisturbance observerradial basis function neural network (RBFNN)adaptive neural output feedback controlasymptotically convergent tracking erroruncertain robot manipulators

Mathematics Subject Classification ID

Feedback control (93B52) Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Control/observation systems with incomplete information (93C41) Adaptive control/observation systems (93C40) Frequency-response methods in control theory (93C80)

Related Items (6)

Nonlinear dynamics analysis and global stabilization of underactuated horizontal spring-coupled two-link manipulator ⋮ Adaptive neural network control of serial variable stiffness actuators ⋮ Adaptive neural network fixed‐time control for an uncertain robot with input nonlinearity ⋮ Adaptive neural impedance control for electrically driven robotic systems based on a neuro-adaptive observer ⋮ LMI-based robust stabilization of a class of input-constrained uncertain nonlinear systems with application to a helicopter model ⋮ Model predictive control of robotic grinding based on deep belief network

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