Robust Adaptive Learning Control for a Class of Nonaffine Nonlinear Systems
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.
Fields of Study & Subjects
Iterative Learning Control Systems
Adaptive Control of Nonlinear Systems
Adaptive Dynamic Programming Control
Publication details
- Journal / source
- IEEE Transactions on Automatic Control
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 71
- Issue
- 7
- Pages
- 4450–4464
- Publication date
- 20 January 2026