emgr—The Empirical Gramian Framework
Computational Methods in Systems and Control Theory Group at the Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, D-39106 Magdeburg, Germany
Algorithms 2018, 11(7), 91; https://doi.org/10.3390/a11070091
Received: 28 May 2018 / Revised: 21 June 2018 / Accepted: 24 June 2018 / Published: 26 June 2018
System Gramian matrices are a well-known encoding for properties of input-output systems such as controllability, observability or minimality. These so-called system Gramians were developed in linear system theory for applications such as model order reduction of control systems. Empirical Gramians are an extension to the system Gramians for parametric and nonlinear systems as well as a data-driven method of computation. The empirical Gramian framework - emgr - implements the empirical Gramians in a uniform and configurable manner, with applications such as Gramian-based (nonlinear) model reduction, decentralized control, sensitivity analysis, parameter identification and combined state and parameter reduction. View Full-Text
Keywords: model reduction; model order reduction; decentralized control; sensitivity analysis; parameter identification; empirical gramians; nonlinear systems; reduced order systems; controllability; observability►▼ Show Figures
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Description: Source code for numerical experiments.
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Himpe, C. emgr—The Empirical Gramian Framework. Algorithms 2018, 11, 91.
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Himpe C. emgr—The Empirical Gramian Framework. Algorithms. 2018; 11(7):91.Chicago/Turabian Style
Himpe, Christian. 2018. "emgr—The Empirical Gramian Framework." Algorithms 11, no. 7: 91.
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