Sequential convex programming for nonlinear optimal control problems in UAV path planning

Usually, an UAV (Unmanned Aerial Vehicle) path planning problem can be modeled as a nonlinear optimal control problem with non-convex constraints in practical applications. However, it is quite difficult to obtain stable solutions quickly for this kind of non-convex optimization with certain converg...

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Veröffentlicht in:	Aerospace science and technology Jg. 76; S. 280 - 290
Hauptverfasser:	Zhang, Zhe, Li, Jianxun, Wang, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Masson SAS 01.05.2018
Schlagworte:	Globally convergent algorithm Non-convex programming Nonlinear optimal control Sequential convex programming UAV path planning UAV path planning Non-convex programming Sequential convex programming Nonlinear optimal control Globally convergent algorithm
ISSN:	1270-9638, 1626-3219
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	Usually, an UAV (Unmanned Aerial Vehicle) path planning problem can be modeled as a nonlinear optimal control problem with non-convex constraints in practical applications. However, it is quite difficult to obtain stable solutions quickly for this kind of non-convex optimization with certain convergence and optimality. In this paper, an algorithm is proposed to solve the problem through approximating the non-convex parts by a series of sequential convex programming problems. Under mild conditions, the sequence generated by the proposed algorithm is globally convergent to a KKT (Karush–Kuhn–Tucker) point of the original nonlinear problem, which is verified by a rigorous theoretical proof. Compared with other methods, the convergence and effectiveness of the proposed algorithm is demonstrated by trajectory planning applications.
ISSN:	1270-9638 1626-3219
DOI:	10.1016/j.ast.2018.01.040