[1]向宏程,邓亦敏,段海滨.基于探索群策略鸽群优化的高超声速飞行器飞/发一体化控制[J].智能系统学报,2022,17(4):849-855.[doi:10.11992/tis.202205033]
XIANG Hongcheng,DENG Yimin,DUAN Haibin.Integrated control of hypersonic aerial vehicle and engine system based on exploring swarm strategy based pigeon inspired optimization[J].CAAI Transactions on Intelligent Systems,2022,17(4):849-855.[doi:10.11992/tis.202205033]
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XIANG Hongcheng,DENG Yimin,DUAN Haibin.Integrated control of hypersonic aerial vehicle and engine system based on exploring swarm strategy based pigeon inspired optimization[J].CAAI Transactions on Intelligent Systems,2022,17(4):849-855.[doi:10.11992/tis.202205033]
基于探索群策略鸽群优化的高超声速飞行器飞/发一体化控制
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
17
期数:
2022年第4期
页码:
849-855
栏目:
吴文俊人工智能科学技术奖论坛
出版日期:
2022-07-05
- Title:
- Integrated control of hypersonic aerial vehicle and engine system based on exploring swarm strategy based pigeon inspired optimization
- Keywords:
- hypersonic aerial vehicle; integrated control of vehicle and engine; pigeon inspired optimization; exploring swarm; altitude control; velocity control; parameter setting; integral time-weighted absolute error
- 分类号:
- TP273
- 摘要:
- 高超声速飞行器飞/发一体化系统具有气流一体化、结构一体化等强飞/发耦合特性，为控制系统的设计带来一定的挑战。针对高超声速飞行器控制系统设计问题，首先在建立高超飞行器飞/发一体化系统模型的基础上，设计了相应的纵向控制律，提出了一种新型的探索群策略鸽群优化算法，并将其应用于高超飞行器飞/发一体化控制参数整定。最后，通过探索群鸽群优化算法对控制参数进行优化，并与基本鸽群优化、粒子群优化进行了对比仿真分析，验证了所提探索群策略鸽群优化算法的可行性和优越性。
- Abstract:
- There are strong coupling characteristics between hypersonic aerial vehicle and engine in the integrated system, such as air flow integration and structure integration, which brings too much challenges to the design of control system. Aiming at the challenge of the design of hypersonic aerial vehicle control system, an integrated flight/launch system model of hypersonic vehicle is established and corresponding longitudinal control law is also designed for this system. An exploring swarm strategy based pigeon inspired optimization algorithm is proposed to overcome the difficulties in debugging the parameters integrated control system. Finally, the control parameters are optimized by the exploring swarm strategy based pigeon inspired optimization algorithm, which is compared with the basic pigeon inspired optimization and particle swarm optimization, verifying the feasibility and superiority of the proposed exploring swarm strategy based pigeon inspired optimization algorithm.
- 参考文献/References:
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- 相似文献/References:
-
[1]冯云山,杨照华.模糊自适应的高超飞行器控制与干扰[J].智能系统学报,2012,7(2):129.
FENG Yunshan,YANG Zhaohua.Control and disturbance analysis of hypersonic vehicles based on fuzzy adaptive[J].CAAI Transactions on Intelligent Systems,2012,7():129.
备注/Memo
收稿日期:2022-05-20。
基金项目:国家自然科学基金项目（U20B2071, U19B2033）
作者简介:向宏程，硕士研究生，主要研究方向为群体智能、高超声速飞行器智能自主飞行控制;邓亦敏，副研究员，主要研究方向为仿生智能感知、无人系统仿生自主飞行控制;段海滨，教授，博士生导师，主要研究方向为无人机自主控制、计算机仿生视觉与智能感知、仿生智能计算理论及应用，曾获吴文俊人工智能科技创新一等奖等，主持国家自然基金重大研究计划重点项目、重点项目等7项。发表学术论文80余篇，出版 专著4部。
通讯作者:段海滨. E-mail：hbduan@buaa.edu.cn
更新日期/Last Update:
1900-01-01