论文:2014,Vol:32,Issue(3):446-450
引用本文:
方群, 王祥. 基于在线RBF神经网络的BTT导弹控制器设计[J]. 西北工业大学
Fang Qun, Wang Xiang. Designing BTT Missile Flight Controller with On-line RBF Neural Network[J]. Northwestern polytechnical university

基于在线RBF神经网络的BTT导弹控制器设计
方群1,2, 王祥1,2
1. 西北工业大学 航天学院, 陕西 西安 710072;
2. 航天飞行动力学国家重点实验室, 陕西 西安 710072
摘要:
针对BTT导弹飞行控制系统的自适应鲁棒控制问题,基于反馈线性化控制和自适应RBF(radical base function)神经网络控制系统设计方法,设计了高精度鲁棒飞行控制器。提出在线权值修正算法,使RBF神经网络能实现对飞行控制系统动态逆误差的在线逼近,进而实现对系统不确定性和外界扰动的实时补偿。通过数值仿真,对所设计的飞行控制器进行了有效性验证。仿真结果表明,相比仅采用反馈线性化控制的飞行控制器,文中提出的飞行控制器能较好地跟踪期望的指令角度信息,鲁棒性能更优。
关键词:    反馈线性化    RBF神经网络    BTT导弹    飞行控制器   
Designing BTT Missile Flight Controller with On-line RBF Neural Network
Fang Qun1,2, Wang Xiang1,2
1. College of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China;
2. National Key Laboratory of Aerospace Flight Dynamics, Xi'an 710072, China
Abstract:
Based on the feedback linearization control and the on-line radical base function (RBF) neural network, we design an adaptive BTT missile flight controller. With the on-line weighted value updating algorithm we pro-posed, the on-line RBF neural network can compensate for uncertainties and disturbances of the BTT missile flight control system through approximating its dynamic inversion errors, thus effectively reducing the coupling of its chan-nels and the inaccuracy of its mathematical model. We simulate the adaptive BTT missile flight controller thus de-signed;the simulation results, and their comparison, show preliminarily that, compared with the flight control sys-tem based on feedback linearization control, the flight controller we designed is more robust and effective for track-ing the desired information on angular command.
Key words:    angular velocity    controllers    design    feedback linearization    flight control systems    functions    missiles    neural networks    robust control    RBF neural networks    BTT missile   
收稿日期: 2013-10-08     修回日期:
DOI:
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作者简介: 方群(1960-),女,西北工业大学教授,主要从事飞行器动力学与控制技术研究。
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