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Tunable Input-to-State Safety with Input Constraints
Ming Li, Jin Chen, Dimos V. Dimarogonas
Tunable input-to-state safety (TISSf) generalizes the input-to-state safety (ISSf) framework by incorporating a tuning function that regulates safety conservatism while preserving…
A Comparative Study of Artificial Potential Fields and Reciprocal Control Barrier Function-based Safety Filters
Ming Li, Zhiyong Sun
In this paper, we demonstrate that controllers designed by artificial potential fields (APFs) can be derived from reciprocal control barrier function quadratic program (RCBF-QP) sa…
A Tunable Universal Formula for Safety-Critical Control
Ming Li, Zhiyong Sun, Patrick J. W. Koelewijn +1
Sontag's universal formula is a widely used technique for stabilizing control through control Lyapunov functions. Recently, it has been extended to address safety-critical control…
Unifying Controller Design for Stabilizing Nonlinear Systems with Norm-Bounded Control Inputs
Ming Li, Zhiyong Sun, Siep Weiland
This paper revisits a classical challenge in the design of stabilizing controllers for nonlinear systems with a norm-bounded input constraint. By extending Lin-Sontag's universal f…
Safe Stabilization with Model Uncertainties: A Universal Formula with Gaussian Process Learning
Ming Li, Zhiyong Sun
A combination of control Lyapunov functions (CLFs) and control barrier functions (CBFs) forms an efficient framework for addressing control challenges in safe stabilization. In our…