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近空间飞行器鲁棒自适应Backstepping控制
引用本文:张强,吴庆宪,姜长生,王玉惠.近空间飞行器鲁棒自适应Backstepping控制[J].系统工程与电子技术,2012,34(4):754-760.
作者姓名:张强  吴庆宪  姜长生  王玉惠
作者单位:1. 南京航空航天大学自动化学院, 江苏 南京 210016;2. 济南大学自动化与电气工程学院, 山东 济南 250022
基金项目:国家自然科学基金(91116017,60974106);国家自然青年科学基金(11102080);航空科学基金(20095152028);南京航空航天大学基本科研业务费专项科研项目(NS2010077,NP2011049);济南大学科研基金(XKY0916)资助课题
摘    要:针对变体近空间飞行器(near space vehiele, NSV)大包络、多模态的特性,研究其姿态的鲁棒自适应跟踪控制问题。首先,提出标称变体NSV切换非线性系统的单一且光滑主控制器设计方法,以解决因飞行模态切换引起的主控制舵面跳变。其次,针对切换瞬间复合干扰存在不连续的问题,给出一组同步切换的改进干扰观测器设计方法。将改进干扰观测器的输出与光滑的主控制律相结合组成不确定变体NSV切换非线性系统的复合控制器。采用平均驻留时间分析法证明所提出的控制方法可以保证闭环不确定变体NSV切换非线性系统的稳定性。最后,仿真结果验证了所提方法的有效性。

关 键 词:近空间飞行器  反演控制  干扰观测器  平均驻留时间  鲁棒自适应控制  径向基神经网络

Robust adaptive backstepping control of near space vehicle
ZHANG Qiang , WU Qing-xian , JIANG Chang-sheng , WANG Yu-hui.Robust adaptive backstepping control of near space vehicle[J].System Engineering and Electronics,2012,34(4):754-760.
Authors:ZHANG Qiang  WU Qing-xian  JIANG Chang-sheng  WANG Yu-hui
Institution:1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;  2. School of Electrical Engineering, University of Jinan, Jinan 250022, China
Abstract:The robust adaptive attitude tracking control problem is studied,aiming at characteristic of near space vehicle(NSV),whose wing sweep angle is variable in the large envelop and multi-modes.Firstly,a smooth master controller is presented for the nominal NSV switched nonlinear systems,in order to solve the controlled variables jumping which is caused by the flight mode switching.Secondly,a class of modified simultaneous switching disturbance observer is designed for the discontinous problem of compound distrubance in switching transient.And a compound controller of uncertain NSV switched nonlinear systems is consisted by the output of modified distrubance observer and the smooth masrer controller.Under the average dwell time,the proposed method can maintain the stability of the closed-loop NSV systems.Finally,the simulation results are presented to show the effectiveness of the proposed scheme.
Keywords:near space vehicle(NSV)  backstepping  disturbance observer(DO)  average dwell time  robust adaptive control  radial basis function neural network(RBFNN)
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