2023/11/01 by Simin Liu, Liu, Simin, Kai S. Yun +5
Engineering · #Advanced Control Systems Optimization #Control Systems and Identification #FOS: Computer and information sciences #FOS: Electrical engineering #Fault Detection and Control Systems #Robotics (cs.RO) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2311.00822
openalex publication_date 2023/11/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
Safe control with guarantees generally requires the system model to be known. It is far more challenging to handle systems with uncertain parameters. In this paper, we propose a generic algorithm that can synthesize and verify safe controllers for systems with constant, unknown parameters. In particular, we use robust-adaptive control barrier functions (raCBFs) to achieve safety. We develop new theories and techniques using sum-of-squares that enable us to pose synthesis and verification as a series of convex optimization problems. In our experiments, we show that our algorithms are general and scalable, applying them to three different polynomial systems of up to moderate size (7D). Our raCBFs are currently the most effective way to guarantee safety for uncertain systems, achieving 100% safety and up to 55% performance improvement over a robust baseline.