Achievable sensitivity bounds for MIMO control systems via an information theoretic approach

DOI10.1016/j.sysconle.2010.10.014zbMath1209.93040OpenAlexW2016755673MaRDI QIDQ627720

Hideaki Ishii, Shinji Hara, Kunihisa Okano

Publication date: 3 March 2011

Published in: Systems \& Control Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sysconle.2010.10.014

zbMATH Keywords

entropyinformation theoryBode's integral formulacontrol systems analysissensitivity properties

Mathematics Subject Classification ID

Sensitivity (robustness) (93B35) Feedback control (93B52) Discrete-time control/observation systems (93C55)

Related Items (6)

Sensitivity minimization, biological homeostasis and information theory ⋮ Design constraints and limits of networked feedback in disturbance attenuation: an information-theoretic analysis ⋮ Minimum error entropy filter for fault detection of networked control systems ⋮ Disturbance attenuation for Markov jump linear system over an additive white Gaussian noise channel ⋮ Mini-workshop: Entropy, information and control. Abstracts from the mini-workshop held March 4--10, 2018 ⋮ Sensitivity analysis of linear continuous-time feedback systems subject to control and measurement noise: an information-theoretic approach

Cites Work

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• Characterization of a complementary sensitivity property in feedback control: an information theoretic approach
• Frequency domain properties of scalar and multivariable feedback systems
• Asymptotically Equivalent Sequences of Matrices and Hermitian Block Toeplitz Matrices With Continuous Symbols: Applications to MIMO Systems
• Properties of sensitivity and complementary sensitivity functions in single-input single-output digital control systems
• Properties of complementary sensitivity function in SISO digital control systems
• Stabilizability of Stochastic Linear Systems with Finite Feedback Data Rates
• Control Over Noisy Channels
• Fundamental Limitations of Disturbance Attenuation in the Presence of Side Information
• Elements of Information Theory

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