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Robust variable horizon model predictive control for vehicle maneuvering
Author(s) -
Richards Arthur,
How Jonathan P.
Publication year - 2006
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.1059
Subject(s) - control theory (sociology) , model predictive control , computer science , bounded function , rendezvous , invariant (physics) , controller (irrigation) , horizon , variable (mathematics) , robust control , mathematical optimization , control engineering , control (management) , control system , spacecraft , engineering , mathematics , artificial intelligence , mathematical analysis , geometry , agronomy , electrical engineering , mathematical physics , biology , aerospace engineering
This paper provides a new method of robust maneuver control with guaranteed finite‐time arrival and satisfaction of constraints, despite the action of an unknown but bounded disturbance. The new method extends the constraint tightening approach to robust model predictive control of constrained linear systems by combining it with a variable horizon . This relaxes the requirement for the target to be an invariant set, which is assumed by many stabilizing MPC formulations but can be restrictive in vehicle maneuvering applications. The target sets for vehicle maneuvers are typically determined by the mission requirements and are not generally invariant sets. The new controller guarantees finite‐time arrival within an arbitrary target set, i.e. not necessarily invariant, and is therefore applicable when the target is predetermined by other factors. Several simulation examples are presented including spacecraft rendezvous control with sensor visibility constraints and UAV guidance through obstacle fields. Copyright © 2006 John Wiley & Sons, Ltd.