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作 者:张科文 潘柏松[1,2] ZHANG Ke-wen;PAN Bai-song(College of Mechanical Engineering,Zhejiang University of Technology,Hangzhou 310023,China;Key Laboratory of Special Purpose Equipment and Advanced Processing Technology,Ministry of Education,Zhejiang University of Technology,Hangzhou 310023,China)
机构地区:[1]浙江工业大学机械工程学院,浙江杭州310023 [2]浙江工业大学特种装备制造与先进加工技术教育部重点实验室,浙江杭州310023
出 处:《浙江大学学报(工学版)》2022年第4期833-842,共10页Journal of Zhejiang University:Engineering Science
基 金:浙江省“尖兵”“领雁”研发攻关计划资助项目(2022C01026);浙江工业大学独立研究项目(2018102007429)。
摘 要:考虑航天器交会模型不确定性的问题,提出基于一般非线性相对运动方程的自适应控制策略.针对复杂非线性系统中由外部扰动及目标星轨道参数引起的线性与非线性不确定性问题,通过自适应神经网络对模型结构进行参数化近似.结合自适应反推技术和李雅普诺夫稳定方法进行自适应控制器设计,能够实现控制目标,保证所得闭环系统的渐近稳定性.为了探究同时存在模型不确定性和输入约束的情况下航天器相对运动的自适应控制设计,提出辅助控制系统来分析和解决输入约束的影响.针对相对运动提出的自适应控制策略保证了闭环系统的稳定性,使得模型未知参数的自适应估计满足最终一致有界性.对不同案例分析比较的数值仿真结果验证了提出控制方法的有效性.An adaptive control strategy based on the general nonlinear relative motion equation was proposed by considering the uncertainty of the spacecraft rendezvous model.A parameterization via adaptive neural networks was implemented for the linear and nonlinear uncertainties in the complex nonlinear system caused by the external disturbances and the orbital parameters of the target spacecraft.Both the backstepping technique and the Lyapunov method were utilized to achieve the control targets and guarantee the asymptotic stability of the resulting closed-loop system.An auxiliary control system was proposed to analyze the effect of input constraints in order to explore the adaptive control design of the spacecraft relative motion in the presence of both model uncertainty and input constraints.The adaptive control strategy proposed for relative motion ensured the stability of the closed-loop system,as well as the uniform ultimate boundedness of the adaptive estimation of the unknown parameters.The effectiveness of the proposed method was verified by the numerical results via the analysis and comparison of different cases.
关 键 词:航天器交会 非线性模型 不确定性 神经网络 自适应控制
分 类 号:V448[航空宇航科学与技术—飞行器设计]
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