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Characterization of Safe Stabilization and Control Lyapunov-Barrier Functions via Zubov Equation Formulation

Yiming Meng, Jun Liu

Abstract

Design and analysis of stabilizing controllers with safety guarantees for nonlinear systems have received considerable attention in recent years. Control Lyapunov-barrier functions (CLBFs) provide a powerful framework for simultaneously ensuring stability and safety; however, their construction for nonlinear systems remains challenging. To address this issue, we build on recent advances in PDE-based characterizations of control Lyapunov functions and Lyapunov-barrier functions for autonomous systems, and propose a succinct Zubov-HJB PDE formulation for safe stabilization of nonlinear control-affine systems under a common compatibility assumption. We further show that the viscosity solution of this PDE yields a maximal CLBF, enabling (not necessarily continuous) feedback synthesis with stability and safety guarantees. In light of recent advances in neural-network-based methods for solving Zubov-type PDEs, this theoretical framework also provides a natural interface to emerging numerical approaches.

Characterization of Safe Stabilization and Control Lyapunov-Barrier Functions via Zubov Equation Formulation

Abstract

Design and analysis of stabilizing controllers with safety guarantees for nonlinear systems have received considerable attention in recent years. Control Lyapunov-barrier functions (CLBFs) provide a powerful framework for simultaneously ensuring stability and safety; however, their construction for nonlinear systems remains challenging. To address this issue, we build on recent advances in PDE-based characterizations of control Lyapunov functions and Lyapunov-barrier functions for autonomous systems, and propose a succinct Zubov-HJB PDE formulation for safe stabilization of nonlinear control-affine systems under a common compatibility assumption. We further show that the viscosity solution of this PDE yields a maximal CLBF, enabling (not necessarily continuous) feedback synthesis with stability and safety guarantees. In light of recent advances in neural-network-based methods for solving Zubov-type PDEs, this theoretical framework also provides a natural interface to emerging numerical approaches.

Paper Structure

This paper contains 12 sections, 3 theorems, 18 equations, 1 figure.

Key Result

Proposition 1

Under Assumption ass: local and ass: h, $\mathcal{D}$ is open and connected. $\blacktriangleleft$$\blacktriangleleft$

Theorems & Definitions (14)

  • Definition 1: Stabilization-with-safety guarantee
  • Definition 2
  • Proposition 1
  • proof
  • Proposition 2
  • proof
  • Corollary 1
  • proof
  • Definition 3
  • proof
  • ...and 4 more