Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

This paper presents two types of nonlinear controllers for an autonomous quadrotor helicopter. One type, a feedback linearization controller involves high-order derivative terms and turns out to be quite sensitive to sensor noise as well as modeling uncertainty. The second type involves a new approach to an adaptive sliding mode controller using input augmentation in order to account for the underactuated property of the helicopter, sensor noise, and uncertainty without using control inputs of large magnitude. The sliding mode controller performs very well under noisy conditions, and adaptation can effectively estimate uncertainty such as ground effects. Recommended by Editorial Board member Hyo-Choong Bang under the direction of Editor Hyun Seok Yang. This work was supported by the Korea Research Foundation Grant (MOEHRD) KRF-2005-204-D00002, the Korea Science and Engineering Foundation(KOSEF) grant funded by the Korea government(MOST) R0A-2007-000-10017-0 and Engineering Research Institute at Seoul National University. Daewon Lee received the B.S. degree in Mechanical and Aerospace Engineering from Seoul National University (SNU), Seoul, Korea, in 2005, where he is currently working toward a Ph.D. degree in Mechanical and Aerospace Engineering. He has been a member of the UAV research team at SNU since 2005. His research interests include applications of nonlinear control and vision-based control of UAV. H. Jin Kim received the B.S. degree from Korea Advanced Institute of Technology (KAIST) in 1995, and the M.S. and Ph.D. degrees in Mechanical Engineering from University of California, Berkeley in 1999 and 2001, respectively. From 2002–2004, she was a Postdoctoral Researcher and Lecturer in Electrical Engineering and Computer Science (EECS), University of California, Berkeley (UC Berkeley). From 2004–2009, she was an Assistant Professor in the School of in Mechanical and Aerospace Engineering at Seoul National University (SNU), Seoul, Korea, where she is currently an Associate Professor. Her research interests include applications of nonlinear control theory and artificial intelligence for robotics, motion planning algorithms. Shankar Sastry received the B.Tech. degree from the Indian Institute of Technology, Bombay, in 1977, and the M.S. degree in EECS, the M.A. degree in mathematics, and the Ph.D. degree in EECS from UC Berkeley, in 1979, 1980, and 1981, respectively. He is currently Dean of the College of Engineering at UC Berkeley. He was formerly the Director of the Center for Information Technology Research in the Interest of Society (CITRIS). He served as Chair of the EECS Department from January, 2001 through June 2004. In 2000, he served as Director of the Information Technology Office at DARPA. From 1996 to 1999, he was the Director of the Electronics Research Laboratory at Berkeley (an organized research unit on the Berkeley campus conducting research in computer sciences and all aspects of electrical engineering). He is the NEC Distinguished Professor of Electrical Engineering and Computer Sciences and holds faculty appointments in the Departments of Bioengineering, EECS and Mechanical Engineering. Prior to joining the EECS faculty in 1983 he was a Professor with the Massachusetts Institute of Technology (MIT), Cambridge. He is a member of the National Academy of Engineering and Fellow of the IEEE.     

一种序贯Unscented卡尔曼滤波在微小型无人直升机导航系统中的应用

对于应用到微小型无人直升机上的低成本捷联惯导（SINS）/GPS组合导航系统来说,SINS Ψ角误差模型在描述低精度惯性器件误差时对误差项的忽略,使其无法满足SINS误差估计的要求.为了克服Ψ角误差模型的不足,本文建立了基于四元数的SINS非线性误差模型.该误差模型无需对失准角进行小角度假设.为了对组合导航系统中的SINS误差进行估计,提出一种序贯Unscented卡尔曼滤波方法.该滤波方法对观测向量进行序贯处理以降低算法的计算量.仿真结果表明,该滤波方法能有效提高低成本SINS/GPS组合导航系统的性能.     

坦克设计新发展

本文提出“针对式坦克发展战略”主要内容,它要求“突破性新概念高新技术”,获得“减法设计方法”,因而形成“坦克发展新道路”.运用“系统总体取胜”的系统工程理论,处理好坦克全系统“综合”、全系统与分系统“配置”、分系统与分系统“匹配”、全系统与人及作战环境“适应”四大关系,以“相互同水平组合”替代“单项高水平爬坡”.通过“从系统总体着眼、由边际零部件突破”的途径,善于从各个部分或部件之间的结合部加以突破,实现坦克设计新发展.     

基于滑动窗口的直升机序列异常检测算法

无标签的序列在异常检测算法中往往存在着对数据的信息掌握不全面、不能合理使用的情况,而采用深度学习的技术实现检测时往往对其计算的解释性欠佳;对于攻克这些难题,以直升机飞行数据为例对时间序列的反常检测问题展开了深入研究,并利用Iforest技术和PCA算法,给出了一个采用滑动窗口的时间序列异常检测方法,利用从滑动窗口采集信息的时间变化状态等数据信息,将序列异常检测问题转换为点异常检测问题;同时以auc评分为衡量标准,从带有时刻特殊标志的多个信息集上检验了检测效率的提高;在无标签的直升机飞行数据集上进行实验,验证了算法的有效性,并通过对比检测过程中不同特征变量的变化情况,从算法层面和现实层面上阐述了算法的可解释性。     

炮控系统的最小方差控制

基于自适应控制原理,将最小方差控制算法应用于炮控系统数字化控制,对行进间火炮在路面谱干扰作用下的响应进行预报．提出了对某坦克炮控系统结构的改进方案．仿真结果表明,这种基于预测的控制算法简单易行,运算速度快,可提高系统控制的有效性     

某型直升机飞行性能仿真建模与验证

主要研究并建立直升机飞行性能仿真模型,在直升机动力学和运动学微分方程的基础上重点解算作用在直升机各部件上的气动力和力矩模型,建立旋翼和尾桨的气动仿真模型,对旋翼挥舞运动进行了分析研究,还考虑了平尾、垂尾、机身和重力的仿真模型。最后通过对各飞行性能指标及其验证原理方法的分析研究,验证了静态性能指标,应用标量指标法验证动态性能指标。     

吊放声纳搜索效能通用仿真模型研究

通过对吊放声纳作战机理的详细分析,以蒙特卡洛法为基础建立了吊放声纳搜索效能的通用仿真模型,并通过仿真实例对模型进行了应用和验证.该模型适用于对各种作战条件下使用各种作战方法时吊放声纳搜索效能的仿真计算.     

基于3D GIS无人直升机地面站系统软件设计与实现

为了实现无人直升机地面站系统的空间数据处理、三维可视化和导航的功能,提出了基于3D GIS无人直升机地面站系统软件设计及其实现的方法.首先对无人直升机的整体系统框架进行说明,然后对地面站系统的软件框架设计和各个功能模块做了详细的分析,在此基础上重点分析了利用World Wind Java软件开发包来实现3D GIS导航的过程.整个地面站软件系统使用Java语言编写,嵌入3DGIS.最后以实例证明了该地面站系统软件的可行性,并且具有良好的可移植性和可扩充性.     

直升机视景仿真及座舱仪表显示系统实现

以开发一套直升机飞行视景仿真系统为目的,提出了一种基于Multigen Creator和Vega软件的三维视景仿真系统解决方案.利用三维图形开发软件Creator对座舱仪表模型进行可视化建模,使用自由度设置(DOF)技术实现仪表指针的动态交互.将模型加载到Vega的环境中,在VC++环境下,基于MFC实现了仪表的驱动程序,给出了具体的实现方法,设计了座舱仪表仿真界面.最后在Vega场景中仿真直升机的飞行状态,直观形象地反映直升机的飞行特性.实际仿真显示,该视是景系统的仿真效果形象逼真,令人满意.     

无人直升机悬停至前飞切换控制

模态切换控制是无人直升机实现全天候自主飞行的关键,实现飞行模态闯快速平稳的切换是无人直升机控制器设计的主要目的。针对无人直升机悬停至前飞过切换程时高度不能保持现象和对象无人直升机高度一航向通道之间存在耦合,提出了前飞速度和航向角速率补偿设计高度通道控制律,升降速度和总距风扇联动关系补偿设计航向通道控制律。最后通过大量仿真试验验证了此方法的可行性和有效性。