Adaptive neural-network sliding mode cascade architecture of longitudinal tracking control for unmanned vehicles

DOI10.1007/s11071-016-3206-2zbMath1373.93174OpenAlexW2549485386MaRDI QIDQ1673961

Keqiang Li, Yugong Luo, Jinghua Guo

Publication date: 27 October 2017

Published in: Nonlinear Dynamics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11071-016-3206-2

zbMATH Keywords

unmanned vehicleslongitudinal vehicle dynamicsspeed tracking controluncertain nonlinearitiesANN-SMC

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Adaptive control/observation systems (93C40) Automated systems (robots, etc.) in control theory (93C85)

Related Items (4)

Barrier Lyapunov functions-based fixed-time stabilization of nonholonomic systems with unmatched uncertainties and time-varying output constraints ⋮ An <scp>LMIs</scp>‐based back‐stepping sliding mode control framework for robust velocity tracking of the automatic driving vehicle on sloped roads ⋮ Finite-time prescribed performance adaptive fuzzy control for unknown nonlinear systems ⋮ Super-twisting algorithm with time delay estimation for uncertain robot manipulators

Cites Work

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• Observer-based adaptive sliding mode control for nonlinear Markovian jump systems
• Cooperative distributed stochastic MPC for systems with state estimation and coupled probabilistic constraints
• Adaptive sliding mode control for a class of MIMO nonlinear systems with uncertainties
• Vehicle Dynamics and Control

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