Robust stop-and-go control strategy: an algebraic approach for non-linear estimation and control
Author(s) -
Jorge Villagrá,
Brigitte D'Andrea Novel,
Sung–Woo Choi,
Michel Fliess,
Hugues Mounier
Publication year - 2009
Publication title -
international journal of vehicle autonomous systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.137
H-Index - 24
eISSN - 1741-5306
pISSN - 1471-0226
DOI - 10.1504/ijvas.2009.033264
Subject(s) - control theory (sociology) , automotive industry , engineering , control engineering , noise (video) , context (archaeology) , aerodynamics , robust control , algebraic number , robustness (evolution) , control (management) , vehicle dynamics , control system , computer science , mathematics , automotive engineering , artificial intelligence , aerospace engineering , paleontology , mathematical analysis , biochemistry , chemistry , electrical engineering , gene , image (mathematics) , biology
International audienceThis paper describes a robust stop-and-go control strategy for vehicles. Since sensors used in a real automotive context are generally low cost, measurements are quite noisy. Furthermore, many vehicle/road interaction factors (road slope, rolling resistance, aerodynamic forces) are very poorly known. Hence, a robust strategy to noise and parameters is proposed within the same theoretical framework: algebraic nonlinear estimation and control techniques. On the one hand, noisy signals will be processed in order to obtain accurate derivatives, and thereafter, variable estimates. On the other hand, a grey-box closedloop control will be implemented to reject all kind of disturbances caused by exogenous parameter uncertainties
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom