基于扩张状态观测器和反步法的四旋翼飞行器姿态控制

四旋翼飞行器在实际执行任务过程中,往往会受到外界的干扰,同时建立模型时的不确定性也会对控制效果产生影响。为了提高系统的鲁棒性,设计了一种基于扩张状态观测器和反步法的姿态控制器。基于牛顿-欧拉方程建立了四旋翼飞行器的数学模型,通过设计扩张状态观测器,以此观测四旋翼飞行器受到的扰动,将观测到的扰动估计值补偿至反步控制器,以减小扰动的影响,改善控制效果。通过数值仿真验证了算法的有效性。     

基于扩张状态观测器的四旋翼吊挂飞行系统非线性控制

针对一类四旋翼飞行器吊挂飞行系统的负载摆动抑制和轨迹跟踪精确控制的问题, 考虑系统存在未知外界扰动和模型动态不确定的情况, 提出一种基于扩张状态观测器(Extended state observer, ESO)的吊挂负载摆动抑制的非线性轨迹跟踪控制方法. 将四旋翼吊挂飞行系统分解为姿态、位置和负载摆动控制三个动态子系统, 分别设计非线性控制器实现欠驱动约束下的解耦控制; 设计一种扩张状态观测器, 用以估计和补偿四旋翼与吊挂负载耦合飞行的未知外界扰动与模型动态不确定性, 并验证了闭环系统的稳定性, 跟踪误差及吊挂负载摆动所有信号的一致最终有界. 最后, 利用Quanser公司的Qball2飞行器进行三维空间螺旋轨迹的跟踪控制, 仿真结果验证了未知干扰下基于扩张状态观测器的四旋翼吊挂飞行非线性控制的有效性和优越性, 实现了四旋翼吊挂系统轨迹跟踪的精确控制和飞行过程中负载摆动的快速抑制.     

基于观测器的伺服系统反馈线性化控制

基于重载且负载大范围变化的伺服系统提出高精度数学模型,建立扩展卡尔曼观测器对速度和模型中参数进行观测,使用基于模型的反馈线性化方法准确地将模型线性化,并使用线性控制方法设计高精度控制器。该策略的应用不但避免了传感器的测量时带来的误差,同时,在参数准确的条件下能够得到更高的控制精度。仿真实验结果表明:运用所设计的基于扩展卡尔曼观测器的反馈线性化控制策略不仅能够准确地对速度状态和参数进行观测,同时系统在跟踪性能方面也取得了较好的结果。     

基于有限时间输出反馈的线性扩张状态观测器

为快速、准确地观测系统中的未知扰动及状态, 提出一种有限时间线性扩张状态观测器(Finite-time linear extended state observer, FT-LESO), 它具有期望的收敛性能且结构简单、易于设计. 假设系统的状态无法量测, 观测器设计问题转化为扰动下的输出反馈控制问题. 针对该问题, 提出一种扰动下的有限时间线性输出反馈控制方法, 得到控制器参数与闭环系统状态向量2-范数间的解析关系. 在此基础上, 提出有限时间线性扩张状态观测器, 得到观测器参数与观测误差收敛速度及稳态观测误差间的解析关系, 给出一充分条件保证观测误差有限时间有界、且能以不低于指数收敛的速度收敛到给定范围内, 为观测器参数设计提供理论依据. 通过数值仿真验证提出的观测器, 仿真结果与理论分析相符, 提出的观测器是有效的.     

基于广义扩张状态观测器的遥操作系统同步控制

针对机械臂遥操作系统中存在的时变时延问题,提出了基于广义扩张状态观测器的控制方法,实现了遥操作系统稳定并且主从机械臂关节角位置同步的控制目标。首先通过反馈线性化,将遥操作系统的主从机械臂动力学模型转化为一个关于位置跟踪误差和时延的状态空间模型。针对该多输入多输出的干扰不匹配模型,设计了广义扩张状态观测器和相应的控制律,从而消除了时变时延以及其它扰动引起的不确定性对系统的影响,并对系统进行稳定性和抗扰性分析。最后,通过仿真验证了所设计的控制方法的有效性。     

基于状态观测器的H-状态反馈控制

本文提出一种基于状态观测器的H_∞曲状态反馈控制,把输出反馈的H_∞控制问题转换成使用状态观测器的H_∞控制问题.通过直接求解状态空间方程,可以获得使用状态观测器的H_∞控制器及其存在的充要条件,它依赖于两个Rjccati方程的解,而且对控制对象的约束不需要满足所谓的正交条件,状态观测器的阶数与控制对象相同,它的输出是控制对象在最坏扰动作用下的状态估计值。     

基于神经网络的非线性扩张状态观测器

自抗扰控制方法是一种新型的非线性设计方法,在自抗扰控制器中主要存在着确定待定参数的问题;非线性扩张状态观测器是自抗扰控制器的核心,在研究非线性扩张观测器中的参数整定问题时,将神经网络的思想引入参数整定,提出了基于神经网络的非线性扩张状态观测器的设计方法,运用该方法可以对任意阶的非线性扩张状态观测器进行参数设计;大量仿真算例表明,设计出的观测器具有良好的鲁棒性,有一定工程应用参考价值.     

基于状态反馈的功率放大器线性化方法

笛卡尔座标反馈线性化技术是减小RF功率放大器非线性失真的一种有效方式,但在高频输入下信号传输延时使系统类似于一高阶系统,严重影响反馈系统的稳定性,一般只适用于窄带系统。为提高系统性能,提出了一种新的状态反馈的线性化技术,并通过二次优化实现参数的优化配置并进行仿真。仿真结果表明通过新方法设计的Cartesian回路增强了系统的稳定性,提高了反馈线性化技术的线性化带宽,而且设计的系统对延时的变化具有较强的鲁棒性。     

基于LESO的MMC-RPC反馈线性化直接功率控制

模块化多电平铁路功率调节器作为一个耦合的多变量非线性系统, 传统PI控制的直接功率控制难以实现对系统的精确解耦. 本文提出了一种基于线性扩张状态观测器的反馈线性化直接功率控制方法, 根据Lie导数构建了模块化多电平铁路功率调节器(MMC-RPC)两输入/两输出功率仿射模型, 设计了精确反馈线性化功率解耦控制器. 针对不确定因素等扰动对精确反馈线性化控制效果的影响, 设计了线性扩张状态观测器对扰动进行观测和补偿, 实现了功率的精确跟踪控制. 最后, 通过MATLAB/Simulink平台搭建仿真模型对所提控制方法进行了验证.     

基于行为的机器人编队控制研究

建立了一种基于行为的机器人编队控制结构模型,该结构采用分层控制策略,全局控制器根据当前所有机器人的状态从一个有限状态机中选择下一步机器人的行为,将协调控制量发送给各机器人,各机器人再通过局部控制器对自身进行控制。该结构模型简单、易行,并且适用于机器人不同任务的需要,具有很高的灵活性,而且易于仿真实现。在此基础上,将一类机器人模型进行反馈线性化,再根据编队控制的要求,利用后推方法设计控制律。仿真结果表明这种结构模型和控制算法是有效的。     

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.     

一种基于反推技术和ESO补偿的解耦控制方法

针对一类非线性多入多出系统,设计了一种新的解耦控制器.首先采用反推技术设计每一个子系统的等效输入;然后用扩张状态观测器(ESO)对各个子系统的耦合、外扰和参数时变等不确定作用进行动态估计,并把估计值引入到反推控制器中进行补偿,最终实现解耦和摔制.利用Lyapunov稳定性理论证明了该方法的收敛性;数例仿真表明了该方法可获得较快的响应速度及较好的解耦效果和鲁棒性.     

On the convergence of an extended state observer for nonlinear systems with uncertainty

The extended state observer first proposed by Jingqing Han in [J.Q. Han, A class of extended state observers for uncertain systems, Control Decis. 10 (1) (1995) 85-88 (in Chinese)] is the key link toward the active disturbance rejection control that is taking off as a technology after numerous successful applications in engineering. Unfortunately, there is no rigorous proof of convergence to date. In this paper, we attempt to tackle this long unsolved extraordinary problem. The main idea is to transform the error equation of objective system with its extended state observer into a asymptotical stable system with a small disturbance, for which the effect of total disturbance error is eliminated by the high-gain.     

基于扩展线性化反馈控制的单级倒立摆仿真

本文引入了基于扩展线性化的非线性反馈控制方法 ,推导了非线性状态反馈控制器的设计 ,并通过对单级倒立摆理想模型的仿真过程中反映出该方法更接近系统实际情况的控制策略。     

The extended Luenberger observer for nonlinear systems

For nonlinear single-input single-output systems , the relationships for a state transformation into the nonlinear observer canonical form are developed. It is possible to dimension a nonlinear observer by an eigenvalue assignment without solving the nonlinear partial differential equations for the transformation, if the transformed nonlinearities are linearized about the reconstructed state. With reference to the extended Kalman filter algorithm, this nonlinear observer design is called the extended Luenberger observer.     

Dynamic Modelling and Stability Analysis of Model-Scale Helicopters Under Wind Gust

The purpose of this paper is to present the stabilization (tracking) with motion planning of a reduced-order model having 3 Degrees Of Freedom (DOF). This last one represents a scale model helicopter mounted on an experimental platform. It deals with the problem of disturbance reconstruction acting on the autonomous helicopter, the disturbance consists in vertical wind gusts. The objective is to compensate these disturbances and to improve the performances of the control. Consequently, a nonlinear simple model with 3DOF of a helicopter with unknown disturbances is used. Three approaches of robust control are compared via simulations: a robust nonlinear feedback control, an active disturbance rejection control based on a nonlinear extended state observer and backstepping control.     

多传感器数据融合下的无人机高度扩张状态观测器设计

无人机在飞行作业时需要精确稳定的高度估计, 针对传感器噪声以及气流和温度变化对无人机高度估计影响的问题, 本文提出一种基于多传感器数据融合的扩张状态观测器设计方法. 首先, 建立无人机高度和传感器噪声模型并对其进行简化处理; 其次, 针对位置传感器、气压计和惯性测量单元的传感器特性, 结合多传感器数据融合方法设计扩张状态观测器估计出无人机高度、z轴速度和总扰动, 并将总扰动估计值反馈给控制系统; 然后, 根据四旋翼无人机非线性数学模型进行数值仿真, 仿真表明本文设计方法的合理性和有效性; 最后, 通过实物测试验证了所设计的扩张状态观测器能有效估计和补偿扰动并对传感器噪声有良好的抑制能力.