Tree-based variable selection for dimensionality reduction of large-scale control systems

Author

Castelletti, Andrea ; Galelli, Stefano ; Restelli, Marcello ; Soncini-Sessa, Rodolfo

Author_Institution

Dept. of Electron. & Inf., Politec. di Milano, Milan, Italy

fYear

2011

fDate

11-15 April 2011

Firstpage

62

Lastpage

69

Abstract

This paper is about dimensionality reduction by variable selection in high-dimensional real-world control problems, where designing controllers by conventional means is either impractical or results in poor performance.

Keywords

hydrodynamics; large-scale systems; mobile robots; nonlinear control systems; pendulums; reduced order systems; set theory; trees (mathematics); wheels; Tono Dam; control variable; coupled 1D hydrodynamic-ecological model; dimensionality reduction; disturbance variables; large-scale control system; model-free variable selection approach; nonlinear dependencies; one-step state transition; ranking algorithm; real-world control problem; recursive variable selection algorithm; state variable; state variables; statistical measure; tree based variable selection; two-wheeled inverted pendulum robot; Aerospace electronics; Computational modeling; Control systems; Estimation; Heuristic algorithms; Input variables; Mathematical model;

fLanguage

English

Publisher

ieee

Conference_Titel

Adaptive Dynamic Programming And Reinforcement Learning (ADPRL), 2011 IEEE Symposium on

Conference_Location

Paris

Print_ISBN

978-1-4244-9887-1

Type

conf

DOI

10.1109/ADPRL.2011.5967387

Filename

5967387