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ESNO-based predefined-time trajectory tracking control for mobile manipulator with full-state constraints
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DOI：10.1177/00202940251400052.png)
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Abstract
En 中文
In this study, the problem of adaptive predefined-time trajectory tracking for mobile manipulator (MMR) subject to external disturbances and full-state constraints is addressed. Firstly, a novel ESN observer (ESNO) with guaranteed predefined-time convergence is proposed, incorporating an adaptive error compensation mechanism to enhance disturbance estimation accuracy. Secondly, an interval-based asymmetric prescribed performance control strategy with a tunable predefined-time prescribed performance function is developed, and its simplified structure reduces computational burden. Thirdly, a predefined-time adaptive filter is designed to avoid the complexity explosion problem. Finally, Lyapunov stability analysis verifies predefined-time convergence of all errors, while numerical simulations and physical MMR platform experiments verify the feasibility and superiority of the algorithm.
Keywords:
mobile manipulator
predefined-time echo state network observer
asymmetric prescribed performance control
predefined-time control
full-state constraints
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