Data-Driven Reference Trajectory Tracking Algorithm and Experimental Validation

Author

Radac, Mircea-Bogdan ; Precup, Radu-Emil ; Petriu, Emil M. ; Preitl, Stefan ; Dragos, Claudia-Adina

Author_Institution

Dept. of Autom. & Appl. Inf., Politeh. Univ. of Timisoara, Timisoara, Romania

Volume

9

Issue

4

fYear

2013

fDate

Nov. 2013

Firstpage

2327

Lastpage

2336

Abstract

This paper proposes a data-driven algorithm that solves a reference trajectory tracking problem defined as an optimization problem. The new data-driven reference trajectory tracking algorithm (DDRTTA) solves the optimization problem in the framework of iterative learning control (ILC). The DDRTTA updates the reference input sequence using an experiment-based approach which accounts for operational constraints and employs an interior point barrier algorithm. Therefore the DDRTTA combines the advantages of data-driven control and ILC. A case study which deals with the angular position control of a nonlinear servo system is included to validate the DDRTTA by experimental and simulation results.

Keywords

iterative methods; learning systems; nonlinear control systems; optimisation; servomechanisms; trajectory control; DDRTTA; ILC; angular position control; data-driven reference trajectory tracking algorithm; experimental validation; iterative learning control; nonlinear servo system; optimization problem; Algorithm design and analysis; Data models; Iterative methods; Optimization; Tracking; Trajectory; Data-driven reference trajectory tracking; experimental results; iterative feedback tuning; iterative learning control; lifted form representation;

fLanguage

English

Journal_Title

Industrial Informatics, IEEE Transactions on

Publisher

ieee

ISSN

1551-3203

Type

jour

DOI

10.1109/TII.2012.2220973

Filename

6339058