Convex Incremental Dissipativity Analysis of Nonlinear Systems - Extended version

Abstract

Efficiently computable stability and performance analysis of nonlinear systems becomes increasingly more important in practical applications. Dissipativity can express stability and performance jointly, but existing results are limited to the regions around the equilibrium points of these nonlinear systems. The incremental framework, based on the convergence of the system trajectories, removes this limitation. We investigate how stability and performance characterizations of nonlinear systems in the incremental framework are linked to dissipativity, and how general performance characterization beyond the ${\mathcal{L}}_2$-gain concept can be understood in this framework. This paper presents a matrix inequalities-based convex incremental dissipativity analysis for nonlinear systems via quadratic storage and supply functions. The proposed dissipativity analysis links the notions of incremental, differential, and general dissipativity. We show that through differential dissipativity, incremental and general dissipativity of the nonlinear system can be guaranteed. These results also lead to the incremental extensions of the ${\mathcal{L}}_2$-gain, the generalized ${\mathcal{H}}_2$-norm, the ${\mathcal{L}}_{\infty }$-gain, and passivity of nonlinear systems.

Original version (without Remark 21, Example 24, and Appendix B) accepted for publication in Automatica

References in corpus (3)

• Pitfalls of Guaranteeing Asymptotic Stability in LPV Control of Nonlinear Systems
• Incremental Stability and Performance Analysis of Discrete-Time Nonlinear Systems using the LPV Framework
• Virtual Control Contraction Metrics: Convex Nonlinear Feedback Design via Behavioral Embedding

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