Projects per year
Abstract
Motivated by a need to characterize transient behaviors in large network systems in terms of relevant signal norms and worst-case input scenarios, we propose a novel approach based on existing theory for matrix pseudospectra. We extend pseudospectral theorems, pertaining to matrix exponentials, to an input-output setting, where matrix exponentials are pre- and post-multiplied by input and output matrices. Analyzing the resulting transfer functions in the complex plane allows us to state new upper and lower bounds on system transients. These are useful for higher-order matrix differential equations, and specifically control of double-integrator networks such as vehicle formation problems. Therefore, we illustrate the theory's applicability to the problem of vehicle platooning and the question of string stability, and show how unfavorable transient behaviors can be discerned and quantified directly from the input-output pseudospectra.
Original language | English |
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Title of host publication | 61st IEEE Conference on Decision and Control |
Pages | 7497 - 7503 |
Number of pages | 7 |
DOIs | |
Publication status | Published - 2022 |
Event | 61st IEEE Conference on Decision and Control (CDC) - Cancún, Mexico Duration: 2022 Dec 6 → 2022 Dec 9 https://cdc2022.ieeecss.org/ |
Conference
Conference | 61st IEEE Conference on Decision and Control (CDC) |
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Country/Territory | Mexico |
City | Cancún |
Period | 2022/12/06 → 2022/12/09 |
Internet address |
Subject classification (UKÄ)
- Control Engineering
Fingerprint
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Performance, Controllability, and Robustness of Large-Scale and Non-Normal Network Systems
Tegling, E. (Researcher), Hansson, J. (Research student) & Govaert, A. (Researcher)
2021/01/01 → 2025/07/31
Project: Research
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Fundamental mechanisms for scalable control of large networks
Tegling, E. (Researcher)
2019/08/01 → 2023/07/31
Project: Research