Title :
Direct data-driven design of sparse controllers
Author :
Formentin, Simone ; Karimi, Alireza
Author_Institution :
Lab. d´Autom., Ecole Polytech. Fed. de Lausanne (EPFL), Lausanne, Switzerland
Abstract :
This paper deals with direct data-driven design of model-reference controllers whose number of parameters is constrained. Input-output (I/O) sparse controllers are introduced and proposed as an alternative to low-order controller tuning. The optimal I/O sparse controller is shown to be never worse than the optimal low-order controller with the same number of parameters and a suited design procedure based on convex optimization is derived. The theoretical concepts are illustrated by means of a benchmark simulation example.
Keywords :
control system synthesis; optimisation; IO; convex optimization; design procedure; direct data-driven design; input-output sparse controllers; model-reference controllers; optimal low-order controller; sparse controllers; Approximation methods; Convex functions; Finite impulse response filters; Random access memory; Standards; Tuning; Vectors;
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4799-0177-7
DOI :
10.1109/ACC.2013.6580307