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Tuning function based adaptive prescribed-time parameter estimation and tracking control design
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DOI：10.1016/j.automatica.2025.112285.png)
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Abstract
En 中文
Most existing prescribed-time (PT) control results focus on the stabilization/regulation problem, with only a few results considering the tracking control problem. In this paper, an adaptive PT tracking control method is proposed for a class of strict feedback nonlinear systems with linearly parametric uncertainties which can be non-vanishing and include both matched and mismatched parts. By using the normalization technique and a novel cutoff function, a two-filter-based parameter estimation error reconstruction mechanism is designed. Furthermore, an improved tuning function based backstepping design solution is provided. Different from the classic tuning function based backstepping results, some additional terms which are designed through the reconstructed parameter estimation errors, are embedded into the virtual control laws, the actual control law and the adaptive laws. Moreover, in order to avoid potential numerical problems in the implementation of the scheme, a modified adaptive PT control scheme is proposed. Finally, two simulation examples are employed to illustrate the effectiveness of the proposed control method. (c) 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
Keywords:
Adaptive control
Parameter estimation
Prescribed-time tracking control
Tuning function