Tuning LQR Controllers: A Sensitivity-Based Approach
Daniele Masti, Mario Zanon, Alberto Bemporad
Abstract
We introduce an approach to efficiently tune LQR controllers for linear time-invariant systems to match a prescribed closed-loop behavior, such as the one given by a reference model. The proposed approach is able to efficiently tune the LQR controller, even for high dimensional systems and is superior in terms of achieved tracking performance and other criteria with respect to global optimization methods commonly used for black-box, simulation-based, automated tuning.
Topics & Concepts
Control theory (sociology)Computer scienceSensitivity (control systems)Controller (irrigation)LTI system theoryClosed loopControl engineeringLinear systemEngineeringControl (management)MathematicsArtificial intelligenceElectronic engineeringAgronomyBiologyMathematical analysisAdvanced Control Systems OptimizationIterative Learning Control SystemsControl Systems and Identification