Bounded invariant verification for time-delayed nonlinear networked dynamical systems. (February 2017)

• Record Type: Journal Article
• Authors: Huang, Zhenqi; Fan, Chuchu; Mitra, Sayan
• Is Part Of: Nonlinear analysis. Volume 23(2017)
• Page Start: 211
• Page End: 229
• Publication Date: 2017-02
• Subjects: Compositional verification -- Delayed dynamical systems -- Simulation-based verification -- Input-to-state stability; Nonlinear functional analysis -- Periodicals; Analyse fonctionnelle non linéaire -- Périodiques; Nonlinear functional analysis; Periodicals; 515.7248
• DOI: 10.1016/j.nahs.2016.05.005
• Languages: English
• ISSNs: 1751-570X

Abstract

Abstract: We present a technique for bounded invariant verification of nonlinear networked dynamical systems with delayed interconnections. The underlying problem in precise bounded-time verification lies with computing bounds on the sensitivity of trajectories (or solutions) to changes in initial states and inputs of the system. For large networks, computing this sensitivity with precision guarantees is challenging. We introduce the notion of input-to-state (IS) discrepancy of each module or subsystem in a larger nonlinear networked dynamical system. The IS discrepancy bounds the distance between two solutions or trajectories of a module in terms of their initial states and their inputs. Given the IS discrepancy functions of the modules, we show that it is possible to effectively construct a reduced (low dimensional) time-delayed dynamical system, such that the trajectory of this reduced model precisely bounds the distance between the trajectories of the complete network with changed initial states. Using the above results we develop a sound and relatively complete algorithm for bounded invariant verification of networked dynamical systems consisting of nonlinear modules interacting through possibly delayed signals. Finally, we introduce a local version of IS discrepancy and show that it is possible to compute them using only the Lipschitz constant and the Jacobian of the dynamic function of the modules.