基于扩张鸽群优化的舰载无人机横侧向着舰自主控制  

Lateral automatic carrier landing control based on expanded pigeon inspired optimization

作　　者：何杭轩 段海滨[1,2] 张秀林 邓亦敏[1] HE Hangxuan;DUAN Haibin;ZHANG Xiulin;DENG Yimin(School of Automation Science and Electrical Engineering,Beihang University,Beijing 100083,China;Peng Cheng Laboratory,Shenzhen 518000,China;Shenyang Aircraft Design and Research Institute,Aviation Industry Corporation of China,Shenyang 110035,China)

机构地区：[1]北京航空航天大学自动化科学与电气工程学院,北京100083 [2]鹏城实验室,广东深圳518000 [3]中国航空工业集团公司沈阳飞机设计研究所,辽宁沈阳110035

出　　处：《智能系统学报》2022年第1期151-157,共7页CAAI Transactions on Intelligent Systems

基　　金：国家自然科学基金项目(91948204,U20B2071,T2121003,U1913602,U19B2033);科技创新2030–“新一代人工智能”重大项目(2018AAA0102403).

摘　　要：舰载无人机着舰会受到舰尾流、航母甲板运动的干扰。为加快无人机在着舰时横侧向响应以及提高舰载机着舰对干扰的鲁棒性,本文提出了一种基于扩张鸽群优化算法的显式模型预测控制方法,并将其应用于舰载机姿态控制器设计,用于解决所设计控制器的参数优化问题。与基本鸽群优化算法、粒子群算法的仿真对比实验表明,相比传统智能优化算法,本文所提出的扩张鸽群优化算法收敛更快,普适性和稳定性也更强,采用显式模型预测控制的舰载无人机着舰系统相比比例-积分-微分控制下的系统响应更快,鲁棒性更强。Carrier landing of unmanned aerial vehicles(UAV)can be disturbed by carrier air wake and deck motion.To improve the response speed and disturbance rejection ability of UAV carrier landing,this paper proposes an explicit model predictive control method based on expanded pigeon inspired optimization(EPIO),and apply it in the design of carrier attitude controler to solve parameter optimization problem of the designed controler.Simulations and comparative experiments are conducted on the proposed basic pigeon inspired optimization algorithm and the particle swarm optimization algorithm,which show quicker rate of convergence,stronger universality and stability of EPIO.The designed control method is verified to be faster and more robust after compared with the proportional-integral-derivative control method.

关 键 词：自动着舰 鸽群优化 姿态控制 舰尾流 甲板运动 显式模型预测 着舰 扩张鸽群优化 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] V249.122[自动化与计算机技术—计算机科学与技术]