Data-Driven Identification of Dissipative Linear Models for Nonlinear Systems-Reference-Cited by-同舟云学术

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Data-Driven Identification of Dissipative Linear Models for Nonlinear Systems

Published:2022-09 Issue:9 Volume:67 Page:4978-4985
ISSN:0018-9286
Container-title:IEEE Transactions on Automatic Control
language:
Short-container-title:IEEE Trans. Automat. Contr.

Author:

Sivaranjani S.¹^ORCID,Agarwal Etika²^ORCID,Gupta Vijay³^ORCID

Affiliation:

1. School of Industrial Engineering, Purdue University, West Lafayette, IN, USA

2. Department of Electrical Engineering, University of Notre Dame, Notre Dame, IN, USA

3. School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA

Funder

Army Research Office

Air Force Office of Scientific Research

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Link

https://ieeexplore.ieee.org/ielam/9/9870073/9792159-aam.pdf

Reference47 articles.

1. An Adaptive Sampling Technique for Passivity Characterization and Enforcement of Large Interconnect Macromodels

2. On the Generation of Large Passive Macromodels for Complex Interconnect Structures

3. First-order-hold sampling of positive real systems and subspace identification of positive real models

4. Bounded Input Dissipativity of Linearized Circuit Models

5. Passivity and Dissipativity Analysis of a System and Its Approximation

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Probability-Based Identification of Hammerstein Systems With Asymmetric Noise Characteristics;IEEE Transactions on Instrumentation and Measurement;2024

2. Learning Dissipative Neural Dynamical Systems;IEEE Control Systems Letters;2023

3. Kernel-Based Models for System Analysis;IEEE Transactions on Automatic Control;2022

4. A Random Path Sampling-based Method for Motion Planning in Many Dimensions;IEEE Transactions on Instrumentation and Measurement;2022

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