Optimal Robust Linear Quadratic Regulator for Systems Subject to Uncertainties

In this technical note, a robust recursive regulator for linear discrete-time systems, which are subject to parametric uncertainties, is proposed. The main feature of the optimal regulator developed is the absence of tuning parameters in online applications. To achieve this purpose, a quadratic cost...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 59; no. 9; pp. 2586 - 2591
Main Authors Terra, Marco H., Cerri, Joao P., Ishihara, Joao Y.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.09.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Closed loop systems
Convergence
Least squares method
Linear quadratic regulator
Mathematical models
Numerical stability
Optimization
Regulators
Robustness
Tuning
Uncertainty
Discrete-time systems
robust regulator
penalty function
min-max problem
least squares
Riccati Equation
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Summary:In this technical note, a robust recursive regulator for linear discrete-time systems, which are subject to parametric uncertainties, is proposed. The main feature of the optimal regulator developed is the absence of tuning parameters in online applications. To achieve this purpose, a quadratic cost function based on the combination of penalty function and robust weighted least-squares methods is formulated. The convergence and stability proofs for the stationary system and a numerical comparative study among the standard linear quadratic regulator, guaranteed cost and H ∞ controllers are provided.
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ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2014.2309282