Safe Adaptive Control for Uncertain Systems with Complex Input Constraints
Abstract
In this paper, we propose a novel adaptive Control Barrier Function (CBF) based controller for nonlinear systems with complex, time-varying input constraints. Conventional CBF approaches often struggle with feasibility issues and stringent assumptions when addressing input constraints. Unlike these methods, our approach converts the input-constraint problem into an output-constraint CBF design. This transformation simplifies the Quadratic Programming (QP) formulation and enhances compatibility with the CBF framework. We design an adaptive CBF-based controller to manage the mismatched uncertainties introduced by this transformation. Our method systematically addresses the challenges of complex, time-varying, and state-dependent input constraints. The efficacy of the proposed approach is validated using numerical examples.
- Publication:
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arXiv e-prints
- Pub Date:
- August 2024
- DOI:
- 10.48550/arXiv.2408.09534
- arXiv:
- arXiv:2408.09534
- Bibcode:
- 2024arXiv240809534D
- Keywords:
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- Electrical Engineering and Systems Science - Systems and Control
- E-Print:
- 8 pages, 2 figures