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Nominal control structure-agnostic model reference adaptive control with performance guarantees
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DOI：10.1080/00207721.2025.2602074.png)
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Abstract
En 中文
The existing model reference adaptive control literature generally considers a nominal control signal in a closed-form and, consequently, relies on the knowledge of the structure of this signal. However, this reliance can be limiting, particularly when this signal is constructed by human operators, artificial intelligence algorithms, real-time optimization techniques, or heuristic-based approaches that lack a closed-form structure. The contribution of this paper is to address this limitation, where a nominal control structure-agnostic model reference adaptive control framework is proposed. Specifically, this framework enables the use of nominal control signals that lack a closed-form structure while preserving the stability of the closed-loop uncertain system with user-defined performance guarantees. In addition to the system-theoretical findings presented, a numerical example involving a human subject demonstrates the efficacy of the proposed framework.
Keywords:
Model reference adaptive control
nominal control structure-agnostic adaptive control
user-defined performance guarantees
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