Computer Science Department
School of Computer Science, Carnegie Mellon University
Revisiting the Complexity of Stability of Continuous and Hybrid Systems
Sicun Gao, Soonho Kong, Edmund M. Clarke
We develop a general framework for obtaining upper bounds on the "practical" computational complexity of stability problems, for a wide range of nonlinear continuous and hybrid systems. To do so, we describe stability properties of dynamical systems in first-order theories over the real numbers, and reduce stability problems to the δ-decision problems of their descriptions. The framework allows us to give a precise characterization of the complexity of different notions of stability for nonlinear continuous and hybrid systems. We prove that bounded versions of the δ-stability problems are generally decidable, and give upper bounds on their complexity. The unbounded versions are generally undecidable, for which we measure their degrees of unsolvability.