Title :
A Data-Driven Approach to Mixed-Sensitivity Control With Application to an Active Suspension System
Author :
Formentin, Simone ; Karimi, Alireza
Author_Institution :
Lab. d´Autom., Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne, Switzerland
Abstract :
In this paper, a data-driven approach is proposed to tune fixed-order controllers for unknown stable LTI plants in a mixed-sensitivity loop-shaping framework. The method requires a single set of input-output samples and it is based on convex optimization techniques; moreover, it asymptotically guarantees the internal stability of the closed-loop system. The effectiveness of the method is illustrated with application to the control of an active suspension system.
Keywords :
H∞ control; T invariance; closed loop systems; control system synthesis; controllers; convex programming; sensitivity analysis; suspensions (mechanical components); active suspension system; closed-loop system; convex optimization technique; data-driven approach; fixed-order controller tuning; input-output samples; internal stability; mixed-sensitivity control; mixed-sensitivity loop-shaping framework; stable LTI plants; Asymptotic stability; Computational modeling; Convex functions; Data models; Sensitivity; Stability criteria; Suspensions; Convex optimization; Youla–Kučera parameterization; data-driven control; identification for control; mixed ${cal H}_2hbox{--}{cal H}_{infty}$ loop-shaping;
Journal_Title :
Industrial Informatics, IEEE Transactions on
DOI :
10.1109/TII.2012.2220556
