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Novel Results on Output-Feedback LQR Design

Adrián Ilka, Nikolce Murgovski

2022IEEE Transactions on Automatic Control24 citationsDOIOpen Access PDF

Abstract

This paper provides novel developments in output-feedback stabilization for linear time-invariant systems within the linear quadratic regulator (LQR) framework. First, we derive the necessary and sufficient conditions for output-feedback stabilizability in connection with the LQR framework. Then, we propose a novel iterative Newton's method for output-feedback LQR design and a computationally efficient modified approach that requires solving only a Lyapunov equation at each iteration step. We show that the proposed modified approach guarantees convergence from a stabilizing state-feedback to a stabilizing output-feedback solution and succeeds in solving high dimensional problems where other, state-of-the-art methods, fail. Finally, numerical examples illustrate the effectiveness of the proposed methods.

Topics & Concepts

Linear-quadratic regulatorControl theory (sociology)Convergence (economics)Output feedbackLyapunov functionFeedback controlQuadratic equationComputer scienceFull state feedbackState (computer science)MathematicsLinear systemOptimal controlMathematical optimizationControl (management)Nonlinear systemControl engineeringAlgorithmEngineeringMathematical analysisQuantum mechanicsPhysicsGeometryEconomicsArtificial intelligenceEconomic growthStability and Control of Uncertain SystemsAdvanced Control Systems OptimizationControl Systems and Identification
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