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Sequential convex programming for nonlinear optimal control problems in UAV path planning
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DOI：10.1016/j.ast.2018.01.040.png)
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Abstract
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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. (C) 2018 Elsevier Masson SAS. All rights reserved.
Keywords:
UAV path planning
Sequential convex programming
Nonlinear optimal control
Globally convergent algorithm
Non-convex programming
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