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 |
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01.05.2018
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Wang, Jun Li, Jianxun Zhang, Zhe |
| Author_xml | – sequence: 1 givenname: Zhe orcidid: 0000-0001-7295-0310 surname: Zhang fullname: Zhang, Zhe organization: Department of Automation, School of Electronic Information and Electric Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai, China – sequence: 2 givenname: Jianxun surname: Li fullname: Li, Jianxun email: lijx@sjtu.edu.cn organization: Department of Automation, School of Electronic Information and Electric Engineering, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai, China – sequence: 3 givenname: Jun surname: Wang fullname: Wang, Jun organization: Luoyang Electronic Equipment Test Center of China, Luoyang, China |
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| SubjectTerms | Globally convergent algorithm Non-convex programming Nonlinear optimal control Sequential convex programming UAV path planning |
| Title | Sequential convex programming for nonlinear optimal control problems in UAV path planning |
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