Persistently Feasible Robust Safe Control by Safety Index Synthesis and Convex Semi-Infinite Programming

Model mismatches prevail in real-world applications. Ensuring safety for systems with uncertain dynamic models is critical. However, existing robust safe controllers may not be realizable when control limits exist. And methods use loose over-approximation of uncertainties, leading to conservative controls. To address these challenges, we propose a control-limits aware framework bounded state-dependent uncertainties. We index synthesis find controller guaranteed under limits. solve via Convex Semi-Infinite Programming, which the tightest formulation convex uncertainties and leads least control. In addition, analyze how can preserved unmodeled Experiment results show that our always much less than strong baselines.