Detecting Nonlinear Modules in a Dynamic Network: A Step-by-Step Procedure

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Abstract

Adopting a dynamic network viewpoint allows one to analyze and identify subsystems of a complex interconnected system. When studying a network of dynamic systems, it is important to know if significant nonlinear behavior is present in a dynamic network under study and where the nonlinearity is located in the network.

This work extends the Best Linear Approximation framework from the closed-loop to the networked setting. The framework is illustrated using a practical step-by-step estimation and analysis procedure. It is shown how nonlinear behavior can be quantified and located in a dynamic network using this framework.

Keywords

Nonlinear Systems
Dynamic Networks
System Identification
Linear Approximation

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This work has received funding from the European Research Council (ERC), Advanced Research Grant SYSDYNET, under the European Unions Horizon 2020 research and innovation programme (grant agreement No 694504).

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