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arXiv · 2602.00968

Robust Adaptive Learning Control for a Class of Non-affine Nonlinear Systems

Shuai Gao·Dong Shen·Abdelhamid Tayebi
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Abstract

We address the tracking problem for a class of uncertain non-affine nonlinear systems with high relative degrees, performing non-repetitive tasks. We propose a rigorously proven, robust adaptive learning control scheme that relies on a gradient descent parameter adaptation law to handle the unknown time-varying parameters of the system, along with a state estimator that estimates the unmeasurable state variables. Furthermore, despite the inherently complex nature of the non-affine system, we provide an explicit iterative computation method to facilitate the implementation of the proposed control scheme. The paper includes a thorough analysis of the performance of the proposed control strategy, and simulation results are presented to demonstrate the effectiveness of the approach.

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Shuai Gao, Dong Shen, Abdelhamid Tayebi. 2026-02-01. Robust Adaptive Learning Control for a Class of Non-affine Nonlinear Systems. https://arxiv.org/abs/2602.00968

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