DocumentCode :
184573
Title :
Reference and command governors: A tutorial on their theory and automotive applications
Author :
Kolmanovsky, Ilya ; Garone, E. ; Di Cairano, Stefano
Author_Institution :
Dept. of Aerosp. Eng., Univ. of Michigan, Ann Arbor, MI, USA
fYear :
2014
fDate :
4-6 June 2014
Firstpage :
226
Lastpage :
241
Abstract :
This paper provides a tutorial overview of reference governors and command governors, which are add-on control schemes for reference supervision and constraint enforcement in closed-loop feedback control systems. The main approaches to the development of such schemes for linear and nonlinear systems are described. The treatment of unmeasured disturbances and parametric uncertainties is addressed. Generalizations to extended command governors, feedforward reference governors, reduced order reference governors, parameter governors, networked reference governors, decentralized reference governors, and virtual state governors are summarized. Examples of applications of these techniques to automotive systems are given. A comprehensive list of references is included. Comments comparing reference and command governor approaches with Model Predictive Control and input shaping, and on future directions in reference and command governor research are included.
Keywords :
automotive engineering; closed loop systems; decentralised control; feedback; feedforward; linear systems; nonlinear control systems; predictive control; reduced order systems; road traffic control; add-on control schemes; automotive systems; closed-loop feedback control systems; command governors; constraint enforcement; decentralized reference governors; feedforward reference governors; input shaping; linear systems; model predictive control; networked reference governors; nonlinear systems; parameter governors; parametric uncertainties; reduced order reference governors; reference supervision; virtual state governors; Automotive engineering; Closed loop systems; Computational modeling; Nonlinear systems; Optimization; Uncertainty; Vectors; Automotive; Constrained control; Predictive control for nonlinear systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
ISSN :
0743-1619
Print_ISBN :
978-1-4799-3272-6
Type :
conf
DOI :
10.1109/ACC.2014.6859176
Filename :
6859176
Link To Document :
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