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Legendre Cooperative PSO Strategies for Trajectory Optimization

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成果类型:
期刊论文
作者:
Liu, Lei;Wang, Yongji*;Xie, Fuqiang;Gao, Jiashi
通讯作者:
Wang, Yongji
作者机构:
[Wang, Yongji; Liu, Lei; Gao, Jiashi] Huazhong Univ Sci & Technol, Natl Key Lab Sci & Technol Multispectral Informat, Sch Automat, Wuhan 430074, Peoples R China.
[Xie, Fuqiang] Univ South China, Sch Elect Engn, Hengyang, Hunan, Peoples R China.
通讯机构:
[Wang, Yongji] H
Huazhong Univ Sci & Technol, Natl Key Lab Sci & Technol Multispectral Informat, Sch Automat, Wuhan 430074, Peoples R China.
语种:
英文
期刊:
Complexity
ISSN:
1076-2787
年:
2018
卷:
2018
页码:
5036791:1-5036791:13
基金类别:
Tis work was supported in part by the National Natural Science Foundation of China (Grants nos. 61573161 and 61473124).
机构署名:
本校为其他机构
院系归属:
电气工程学院
摘要:
Particle swarm optimization (PSO) is a population-based stochastic optimization technique in a smooth search space. However, in a category of trajectory optimization problem with arbitrary final time and multiple control variables, the smoothness of variables cannot be satisfied since the linear interpolation is widely used. In the paper, a novel Legendre cooperative PSO (LCPSO) is proposed by introducing Legendre orthogonal polynomials instead of the linear interpolation. An additional control variable is introduced to transcribe the original ...

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