DocumentCode :
635080
Title :
A new method of direct data-driven predictive controller design
Author :
Hua Yang ; Shaoyuan Li
Author_Institution :
Coll. of Inf. Sci. & Eng., Ocean Univ. of China, Qingdao, China
fYear :
2013
fDate :
23-26 June 2013
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, we try to find a direct path between data and predictive controller. A straightforward data-driven predictive controller for the linear multivariable systems is proposed, without identifying any representation of the system in an intermediate step. The minimal image representation is used to describe the controlled linear multivariable system instead of model or dynamical description matrix. Data-based prediction can be estimated directly from an input/output trajectory of the system and thus the computation of dynamic optimization. For the unconstrained condition, control laws can be analytically determined directly from the data Hankel matrices without model or any intermediate step to meet the given performance specifications. The proposed predictive controller is demonstrated on a multivariable system.
Keywords :
Hankel matrices; control system synthesis; image representation; linear systems; multivariable systems; predictive control; control laws; controlled linear multivariable system; data Hankel matrices; direct data-driven predictive controller design method; direct path; dynamical description matrix; minimal image representation; system input-output trajectory; Computational modeling; Data models; Optimization; Predictive control; Predictive models; Trajectory; Vectors; Data driven approach; Model free; Optimization order reduction; Predictive control; off-set free tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (ASCC), 2013 9th Asian
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-5767-8
Type :
conf
DOI :
10.1109/ASCC.2013.6606233
Filename :
6606233
Link To Document :
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