Comparison of Non-deterministic Linear Systems by $(\gamma,\delta)$-Similarity
Armin Pirastehzad, Arjan van der Schaft, Bart Besselink

TL;DR
This paper introduces a new measure called $(\gamma,\delta)$-similarity for comparing stable linear systems based on their input-output behavior, enabling better analysis and synthesis of interconnected systems.
Contribution
It defines $(\gamma,\delta)$-similarity as a behavioral approximation measure, characterizes it via linear matrix inequalities, and demonstrates its compositional properties for system analysis.
Findings
$(\gamma,\delta)$-similarity can be characterized by LMIs.
The measure is preserved under series and feedback interconnections.
Application demonstrated on an electrical network example.
Abstract
We introduce -similarity, a notion of system comparison that measures to what extent two stable linear dynamical systems behave similarly in an input-output sense. This behavioral similarity is characterized by measuring the sensitivity of the difference between the two output trajectories in terms of the external inputs to the two potentially non-deterministic systems. As such, -similarity is a notion that characterizes \emph{approximation} of input-output behavior, whereas existing notions of simulation target equivalence. Next, as this approximation is specified in terms of the signal norm, -similarity allows for integration with existing methods for analysis and synthesis of control systems, in particular, robust control techniques. We characterize the notion of -similarity as a linear matrix inequality…
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Taxonomy
TopicsFormal Methods in Verification · Petri Nets in System Modeling · Logic, programming, and type systems
