Design of Fractional‐Order Backstepping Sliding Mode Control for Quadrotor UAV

This paper derives a nonlinear translational and rotational dynamic model of the quadrotor UAV. An original fractional‐order backstepping sliding mode control method for a typical quadrotor UAV is presented. The new approach can decrease the chattering phenomenon and increase the robustness of control strategy. The strongly coupled characteristics of the under‐actuated system are sought by the virtual controllers. The feasibility for different track trajectories are verified using MATLAB. The new control method can not only track the expected trajectory very well but also has a better robustness for different complex trajectory under disturbances, as the simulation results demonstrate.     

Finite-time Adaptive Integral Backstepping Fast Terminal Sliding Mode Control Application on Quadrotor UAV

International Journal of Control, Automation and Systems - This paper presents a reliable and novel quadrotor flight control system designed to enhance trajectory tracking performance, robustness...     

Modeling and Robust Backstepping Sliding Mode Control with Adaptive RBFNN for a Novel Coaxial Eight-rotor UAV

This paper focuses on the robust attitude control of a novel coaxial eight-rotor unmanned aerial vehicles (UAV) which has higher drive capability as well as greater robustness against disturbances than quad-rotor UAV. The dynamical and kinematical model for the coaxial eight-rotor UAV is developed, which has never been proposed before. A robust backstepping sliding mode controller (BSMC) with adaptive radial basis function neural network (RBFNN) is proposed to control the attitude of the eightrotor UAV in the presence of model uncertainties and external disturbances. The combinative method of backstepping control and sliding mode control has improved robustness and simplified design procedure benefiting from the advantages of both controllers. The adaptive RBFNN as the uncertainty observer can effectively estimate the lumped uncertainties without the knowledge of their bounds for the eight-rotor UAV. Additionally, the adaptive learning algorithm, which can learn the parameters of RBFNN online and compensate the approximation error, is derived using Lyapunov stability theorem. And then the uniformly ultimate stability of the eight-rotor system is proved. Finally, simulation results demonstrate the validity of the proposed robust control method adopted in the novel coaxial eight-rotor UAV in the case of model uncertainties and external disturbances.      

永磁同步电机的自适应反演滑模变结构控制

针对永磁同步电机提出一种基于反演的PMSM自适应滑模控制方案.设计基于反演的滑模变结构位置控制器,通过RBF神经网络实现系统参数变化和外部负载扰动等引起的不确定上界值的在线辨识,减小滑模控制器的控制量,并引入饱和函数来减弱系统的"抖动"现象.理论分析和仿真结果对比表明,基于RBF神经网络的自适应反演滑模控制对参数变化和外部负载扰动具有很好的鲁棒性,永磁同步电动机获得了很好的跟踪效果.     

Higher Order Sliding Mode Controllers With Optimal Reaching

Higher order sliding mode (HOSM) control design is considered for systems with a known permanent relative degree. In this paper, we introduce the robust Fuller's problem that is a robust generalization of the Fuller's problem, a standard optimal control problem for a chain of integrators with bounded control. By solving the robust Fuller's problem it is possible to obtain feedback laws that are HOSM algorithms of generic order and, in addition, provide optimal finite-time reaching of the sliding manifold. A common difficulty in the use of existing HOSM algorithms is the tuning of design parameters: our methodology proves useful for the tuning of HOSM controller parameters in order to assure desired performances and prevent instabilities. The convergence and stability properties of the proposed family of controllers are theoretically analyzed. Simulation evidence demonstrates their effectiveness.     

基于扰动观测器的机械臂自适应反演滑模控制

机械臂的动力学模型通常包含一定的结构不确定性,并受到外界未知干扰的影响。针对现有模型的不确定性特点,提出了一种基于非线性扰动观测器的自适应反演滑模控制方法,解决机械臂的轨迹跟踪控制问题。对于外界干扰,利用非线性扰动观测器进行观测补偿,无需上界先验知识;对于结构不确定性,引入反演滑模控制,同时设计自适应律,保证闭环系统的稳定性并增强系统的动态适应性。仿真结果证明,所提出的方法可以有效克服系统不确定性,降低控制输入信号的抖振,最终实现期望轨迹的快速精确跟踪。     

Transition Flight Modeling of a Fixed-Wing VTOL UAV

This paper describes a complete six-degree-of-freedom nonlinear mathematical model of a tilt rotor unmanned aerial vehicle (UAV). The model is specifically tailored for the design of a hover to forward flight and forward flight to hover transition control system. In that respect, the model includes the aerodynamic effect of propeller-induced airstream which is a function of cruise speed, tilt angle and angle of attack. The cross-section area and output velocity of the propeller-induced airstream are calculated with momentum theory. The projected area on the UAV body that is affected by the propeller-induced airstream is specified and 2D aerodynamic analyses are performed for the airfoil profile of this region. Lookup-tables are generated and implemented in the nonlinear mathematical model. In addition, aerodynamic coefficients of the airframe are calculated by using CFD method and these data are embedded into the nonlinear model as a lookup-table form. In the transition flight regime, both aerodynamic and thrust forces act on the UAV body and the superimposed dynamics become very complex. Hence, it is important to define a method for hover-to-cruise and cruise-to-hover transitions. To this end, both transition scenarios are designed and a state-schedule is developed for flight velocity, angle of attack, and thrust levels of each of the thrust-propellers. This transition state schedule is used as a feedforward state for the flight control system. We present the simulation results of the transition control system and show the successful transition of TURAC in experiment.     

水平欠驱动机械臂的反步自适应滑模控制

针对二自由度水平欠驱动机械臂系统,提出了基于分层滑模控制思想的反步自适应滑模控制方法．该方法能够在不对系统状态模型进行复杂坐标变换,并且没有约束方程限制的前提下实现对欠驱动系统的反馈滑模控制．仿真结果表明了该方法的有效性,而且优化后的控制器具有较好的适应性和控制效果．     

飞行仿真转台伺服系统的反演自适应滑模控制(英文)

采用滑模控制对非线性系统进行控制时,抖振是不可避免的现象,如何抑制抖振成为研究的重点。介绍了一种反演自适应滑模控制方案,它可以解决非线性系统中的不确定性问题,保证系统的鲁棒性。为此,首先介绍了反演设计的原理,通过在反演设计中引入滑模控制,并采用自适应算法对不确定性进行估计,有效的降低了抖振。最后给出了一个应用此方法进行控制的实际例子,结果表明了这种方法的有效性。     

非匹配不确定系统的自适应反演准滑模控制

对于一类n阶非线性系统,提出一种自适应反演准滑模控制方法,控制的前n-1步采用自适应反演算法消除非匹配不确定性的影响,在最后一步,为改进跟踪效果,结合了可变边界层的思想,设计了准滑模控制方法,达到系统的n个状态快速收敛的目的.最终系统中不满足匹配条件的部分也具有较好的鲁棒性.与自适应反演线性滑模方法相比具有更好的跟踪性,理论分析证明了控制系统在削弱抖振的同时也能保证稳态精度,仿真实验证明了该方法的可行性.     

机械臂自适应反演超螺旋全局终端滑模控制

针对机械臂系统存在的系统参数摄动、非线性摩擦及外部干扰等不确定问题,提出一种自适应反演超螺旋全局终端滑模轨迹跟踪控制方法。该方法基于反演法、Lyapunov理论和全局快速终端滑模理论设计控制器,保证系统稳定性及全局收敛性,增强系统的鲁棒性。为解决系统集总扰动上界未知的问题,采用自适应技术设计切换控制律,抵消不确定性的影响,同时引入超螺旋算法抑制滑模控制固有的抖振现象。最后,通过理论分析和仿真算例验证了该控制器的有效性与可行性。     

分散自适应模糊滑模控制器的设计与分析

研究了一类具有函数控制增益的耦合大系统的分散自适应模糊控制问题 ,提出了能够利用专家的语言信息和数字信息的分散自适应模糊滑模控制器的设计方案 .通过理论分析 ,证明了分散自适应模糊控制系统是全局稳定的 ,跟踪误差可收敛到零的一个邻域内     

Sliding Mode and PI Controllers for Uncertain Flexible Joint Manipulator

This paper is dealing with the problem of tracking control for uncertain flexible joint manipulator robots driven by brushless direct current motor(BDCM). Flexibility of joint in the manipulator constitutes one of the most important sources of uncertainties. In order to achieve high performance, all parts of the manipulator including actuator have been modeled. To cancel the tracking error, a hysteresis current controller and speed controllers have been developed. To evaluate the effectiveness of speed controllers, a comparative study between proportional integral(PI) and sliding mode controllers has been performed. Finally, simulation results carried out in the Matlab simulink environment demonstrate the high precision of sliding mode controller compared with PI controller in the presence of uncertainties of joint flexibility.     

不确定非线性系统的多模反演滑模控制

对一般形式的仿射非匹配不确定非线性系统,研究了一种具有任意小跟踪误差的稳定控制器的新方法,结合反演（backstepping）设计和变结构控制,提出了反演变结构控制策略,对存在非匹配的不确定性和未知干扰的系统,设计的反演结构控制器实现了鲁棒输出跟踪,闭环系统在有限时间进入滑动模态,仿真算例证实了理论结果。     

基于RBFNN的风电机组变桨距反推滑模控制

在风力发电变桨距优化控制问题的研究中,针对具有不确定性的非线性风电机组,设计了基于径向基函数神经网络(RBFNN)的风电机组变桨距反推滑模控制器.首先应用精确反馈线性化理论将原非线性系统模型进行全局线性化处理,再应用RBFNN对不确定项进行逼近,结合滑模控制和反推法,设计反推滑模控制器(BSMC),保证了高风速下风机的稳定性,抑制了不确定项对系统的影响,避免了传统反推法存在的计算复杂问题.通过与传统滑模控制器(SMC)进行仿真对比,结果表明,RBFNN-BSMC能够很好地稳定风电机组的输出功率,具有较强的鲁棒性.     

四旋翼飞行器姿态的自适应反演滑模控制研究

微小型四旋翼飞行器是一种欠驱动、强耦合的非线性系统.针对四旋翼飞行器控制中的姿态控制优化进行研究,建立了四旋翼飞行器完整的姿态运动模型,为提高系统响应速度和抗干扰性,在反演控制基础上与自适应和滑模控制方法相结合,根据Lyapunov稳定性进行控制系统设计,并选取合适的控制参数使所设计的控制系统是渐进稳定的,最终设计了一种基于自适应反演滑模算法的姿态控制器.通过计算机仿真软件进行验证,结果表明所设计的控制器与其它算法相比具有更快的响应时间和很强的鲁棒性.     

独立线控转向电机转角自适应反演滑模控制

针对独立线控转向系统中转向直流电机控制精度低、响应速度慢的问题,以独立线控转向系统转向电机为控制对象,采用自适应反演滑模控制(ABSMC)算法对转向电机转角进行跟踪控制.通过反步法推导控制律,并利用Lyapunov理论证明了闭环系统的稳定性.应用Carsim与Simulink的联合仿真,以横摆角速度不变的变传动比控制为...     

基于反步积分滑模摩擦补偿的光电伺服转台控制

针对光电伺服转台在目标搜索、瞄准时出现角度跟踪误差较大、爬行、抖振等问题,本文结合反步法、自适应滑模、LuGre模型的优势,提出了一种反步自适应积分滑模摩擦补偿控制策略。首先根据光电伺服转台工作环境复杂多变的特点,引入环境因子,建立了改进的LuGre模型,然后在李雅普诺夫框架下分步设计子系统与控制律。引入多个自适应律消除参数不确定对系统的影响,采用双非线性摩擦观测器进行摩擦扰动补偿,采用积分滑模增强系统鲁棒性并减小系统稳态误差。由李雅普诺夫定理证明可知系统全局稳定。仿真结果表明,这种新型控制策略能有效抑制摩擦扰动,提高系统角度跟踪精度,可以满足光电伺服转台的高精度跟踪控制的要求。     

基于自回归小波神经网络的感应电动机滑模反推控制

为了提高感应电动机控制的鲁棒性, 提出了一种新颖的感应电动机解耦模型. 基于感应电动机的解耦模型, 利用滑模控制和反推控制设计电动机的虚拟转矩和磁链电压控制器. 滑模开关增益的大小是造成系统抖振的关键, 采用自回归小波神经网络(Self-recurrent wavelet neural networks, SRWNN)在线估计滑模开关增益的大小可以有效降低滑模控制造成的抖振. 仿真结果表明基于SRWNN在线估计滑模开关增益的滑模反推控制方案可以有效提高感应电动机控制的鲁棒性, 同时降低了滑模控制造成的抖振.     

基于反演自适应动态滑模的气垫船航向控制

针对全垫升气垫船运动非线性明显、可操纵性差,为改善操控水平,能够准确地按给定航向航行,设计了反演自适应动态滑模的航向控制算法。建立了三自由度全垫升气垫船平面运动数学模型,并给出了航向非线性控制模型。将反演方法与动态滑模相结合,设计新型切换函数,以实现航向的平滑、无抖振控制。最后,在不同外界扰动作用下进行了仿真,试验结果表明,所设计航向控制算法能够提高全垫升气垫船航向的控制精度,具有自适应性强、响应速度快、稳定性好等特点。