Path tracking control of a self-driving wheel excavator via an enhanced data-driven model-free adaptive control approach

DOI10.1049/iet-cta.2018.5493zbMATH Open1544.93361MaRDI QIDQ6598707

Shida Liu, Zhidong Deng, Lei Guo, Taotao Tian, Zhongsheng Hou

Publication date: 5 September 2024

Published in: IET Control Theory \& Applications (Search for Journal in Brave)

zbMATH Keywords

stabilitytime delaytrackingadaptive controltime-varying systemsnonlinear control systemsmotion controlposition controltime-varying parameterJacobian matricescontrol system synthesispath tracking control problemlinearisation techniquespseudo-Jacobian matrixmaximum tracking errordriving tasksdynamical linearisation techniqueEMFAC-TD methodenhanced data-driven model-free adaptive control approachexcavator driving dynamicsexcavator dynamicsexcavatorsmultiinput and multioutput systemsoutput datapreview-deviation-yaw-based methodSmith estimating methodwheel excavator

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Multivariable systems, multidimensional control systems (93C35) Adaptive control/observation systems (93C40) Delay control/observation systems (93C43)

Cites Work

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• Dynamic modeling, predictive control and performance monitoring. A data-driven subspace approach
• Data-driven model-free adaptive sliding mode control for the multi degree-of-freedom robotic exoskeleton
• Lazy learning for local modelling and control design
• Iterative feedback tuning—an overview
• Direct Nonlinear Control Design: The Virtual Reference Feedback Tuning (VRFT) Approach

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