Minimum-energy covariance controllers

DOI10.1016/S0005-1098(96)00188-4zbMath0879.93056OpenAlexW2176624840WikidataQ127186305 ScholiaQ127186305MaRDI QIDQ1361308

Grigoriadis, Karolos M., Robert E. Skelton

Publication date: 23 July 1997

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0005-1098(96)00188-4

zbMATH Keywords

optimal stochastic controlcovariance assignment controllers

Mathematics Subject Classification ID

Feedback control (93B52) Discrete-time control/observation systems (93C55) Optimal stochastic control (93E20)

Related Items (8)

Finite-horizon covariance control for discrete-time stochastic linear systems subject to input constraints ⋮ Unnamed Item ⋮ A moment-based approach for nonlinear stochastic tracking control ⋮ Linear quantum systems with diagonal passive Hamiltonian and a single dissipative channel ⋮ Robust variance-constrained control for a class of continuous time-delay systems with parameter uncertainties ⋮ Output feedback robust \(H \infty\) control with \(D\)-stability and variance constraints: Parametrization approach ⋮ Stochastic Control Liaisons: Richard Sinkhorn Meets Gaspard Monge on a Schrödinger Bridge ⋮ Robust satisfactory fault-tolerant control of uncertain linear discrete-time systems: an LMI approach

Cites Work

• Unnamed Item
• Covariance controllers: A new parametrization of the class of all stabilizing controllers
• Alternating convex projection methods for discrete-time covariance control design
• A generalized solution of the orthogonal Procrustes problem
• Covariance control theory
• L-structured matrices and linear matrix equations^∗
• Matrix Analysis
• Optimal controllers for finite wordlength implementation
• Liapunov and covariance controllers
• Modern Wiener-Hopf design of optimal controllers--Part II: The multivariable case
• Minimal energy covariance control
• Alternating convex projection methods for covariance control design
• A theory of state covariance assignment for discrete systems
• The matrix minimum principle

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