Iterative-learning-based tracking control of a two-wheeled mobile robot with model uncertainties and unknown periodic disturbances

DOI10.1016/J.JFRANKLIN.2024.106962zbMATH Open1543.93082MaRDI QIDQ6577427

Lin Yu, Junlin Xiong, Min Xie

Publication date: 23 July 2024

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

zbMATH Keywords

wheeled mobile robotadaptive controlrobust controlmodel uncertainty

Mathematics Subject Classification ID

Adaptive control/observation systems (93C40) Perturbations in control/observation systems (93C73) Automated systems (robots, etc.) in control theory (93C85) Iterative learning control (93B47)

Cites Work

• Trajectory tracking control for wheeled mobile robots based on nonlinear disturbance observer with extended Kalman filter
• Robust trajectory tracking control of non-holonomic wheeled mobile robots using an adaptive fractional order parallel fuzzy PID controller
• Robust adaptive trajectory tracking for wheeled mobile robots based on Gaussian process regression
• Design and implementation of a block-backstepping based tracking control for nonholonomic wheeled mobile robot
• Robust neural network–based tracking control and stabilization of a wheeled mobile robot with input saturation
• A new adaptive tracking control scheme of wheeled mobile robot without longitudinal velocity measurement
• Dual closed‐loop tracking control for wheeled mobile robots via active disturbance rejection control and model predictive control
• Nonlinear Adaptive Learning Control With Disturbance of Unknown Periods
• Adaptive Constrained Formation-Tracking Control for a Tractor-Trailer Mobile Robot Team With Multiple Constraints
• Globally exponentially convergent velocity observer design for mechanical systems with nonholonomic constraints
• Neural networks‐based sliding mode tracking control for the four wheel‐legged robot under uncertain interaction
• Model predictive tracking control with disturbance compensation for wheeled mobile robots in an environment with obstacles

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