基于SMDO的滑模控制器设计及其在导弹上的应用

提出了一种基于滑模干扰观测器(SMDO)的滑模控制器(SMC)设计方法.针对一类级联多输入多输出(MI-MO)非线性系统,根据奇异摄动原理将其分为内、外回路分别进行控制器设计.以外回路为例,分析了传统基于饱和函数的滑模控制的鲁棒性,针对其在面I临干扰时鲁棒性较差的问题,在名义滑模控制律的基础上设计了基于超扭曲算法的SM...     

翻滚非合作目标逼近与跟踪的轨道和姿态控制

面向近距离逼近与捕获翻滚非合作目标的在轨服务空间清理任务需求,研究了航天器非合作式交会对接的轨道和姿态控制问题。在控制输入受限约束下,考虑存在参数不确定性和外部扰动的情况,结合滑模控制和自适应控制技术,分别进行鲁棒自适应位置和姿态控制器设计。利用自适应控制估计参数不确定性、未知干扰上界以及滑模控制反馈系数矩阵,提高了系统的鲁棒性。通过李雅普诺夫理论证明了系统在控制器作用下全局一致最终有界稳定。仿真结果验证了控制器的有效性,能够有效解决与高速旋转非合作目标的稳定相对位姿关系建立的难题。     

执行器故障的挠性航天器姿态滑模容错控制

针对挠性航天器执行器卡死与失效故障的姿态稳定控制问题,提出一种改进型滑模容错控制策略.与传统的滑模控制相比,该方法能削弱传统滑模控制中抖振现象对姿态控制精度的影响,且它采用自适应技术在线估计系统中的不确定参数,从而保证控制性能对外部干扰、不确定甚至时变转动惯量具有良好的鲁棒性.该控制器并不需要任何在线或离线的故障信息,...     

基于名义模型的飞行模拟转台反演滑模控制

针对飞行模拟转台这一实际的不确定伺服系统,提出一种新型控制策略,该控制策略是建立在名义模型基础上的一种新型全鲁棒滑模控制器.控制系统由两种控制器构成,一种是针对实际对象的全鲁棒滑模控制器,另一种是针对名义模型的积分反演滑模控制器.采用名义模型与实际对象之间的建模误差设计全鲁棒滑模控制器,采用积分反演滑模控制器来保证控制精度,全鲁棒性能由全局滑模控制器来保证.采用Lyapunov方法实现了两种控制器的稳定性分析.以飞行模拟转台伺服系统为被控对象,针对正弦和阶跃响应的仿真结果表明,采用所提出的控制方法,可实现全局鲁棒性并保证较高的位置跟踪精度.     

Fixed-time adaptive model reference sliding mode control for an air-to-ground missile

This paper addresses the fixed-time adaptive model reference sliding mode control for an air-to-ground missile associated with large speed ranges, mismatched disturbances and un-modeled dynamics. Firstly, a sliding mode surface is developed by the tracking error of the state equation and the model reference state equation with respect to the air-to-ground missile. More specifically,a novel fixed-time adaptive reaching law is presented. Subsequently, the mismatched disturbances and the un-modeled dynamics are treated as the model errors of the state equation. These model errors are estimated by means of a fixed-time disturbance observer, and they are also utilized to compensate the proposed controller. Therefore, the fixed-time controller is obtained by an adaptive reaching law and a fixed-time disturbance observer. Closed-loop stability of the proposed controller is established. Finally, simulation results including Monte Carlo simulations, nonlinear six-DegreeOf-Freedom(6-DOF) simulations and different ranges are presented to demonstrate the efficacy of the proposed control scheme.     

考虑输入饱和的固定翼无人机自适应增益滑模控制

针对复杂环境下的固定翼无人机飞行控制问题，考虑输入饱和以及复杂外界干扰的影响，提出一种基于自适应滑模控制方法的固定翼无人机飞行控制策略。首先，对固定翼无人机模型进行介绍，将模型分为姿态子系统和速度子系统；其次，针对姿态子系统和速度子系统的特点以及控制需求，分别采用自适应多变量螺旋滑模和自适应快速超螺旋滑模设计姿态控制器和速度控制器，该策略无需设计干扰观测器对外界干扰进行估计，仍然可以实现固定翼无人机对姿态参考指令和速度参考指令的有限时间精确跟踪，并基于Lyapunov的稳定性分析方法证明了闭环系统的稳定性。最后，对本文所提出的控制策略进行了仿真验证，结果表明该控制策略具有良好的控制性能。     

不确定航空发动机分布式控制系统自适应滑模控制

针对存在参数摄动、外部干扰的航空发动机不确定性分布式控制系统，在系统具有时变输入时延和干扰上界未知的情况下，设计了具有鲁棒性能的自适应滑模控制器。基于预测控制和矩阵奇异值理论，对初始的发动机离散分布式模型进行等效线性变换，得到不显含时延项的规范形系统模型，便于进行滑模面参数的求解；在给定的H∞指标下，推导了滑模运动在非匹配不确定性作用下渐进稳定的充分条件，给出了线性矩阵不等式(LMI)形式的滑模面参数设计方法；最后，设计对干扰具有估计功能的自适应率，在此基础上提出自适应滑模控制器。仿真结果表明:所设计的控制器能够有效降低外部干扰对系统动态性能的影响，在所考虑的不确定性因素作用下，系统的滑模运动具有理想的H∞性能。当外部干扰强度变化时，控制器的鲁棒性较好，状态收敛时间小于0.8s，且不存在抖振。      

基于自适应反演的导弹滑模控制

阐述了在导弹系统存在不确定性情况下,基于自适应反演控制技术和模糊神经网络理论,提出了一种导弹滑模控制系统设计方法。设计过程中将不确定性对系统的影响合成为一项,然后应用模糊神经逼近器来逼近系统的不确定项;考虑了已知信息,利用自适应模糊神经控制理论和滑模控制设计了控制器,应用Lypunov稳定性理论保证了闭环系统的稳定性,并推导出模糊神经逼近器各参数的自适应调节律。     

对失控航天器在轨服务的自适应滑模控制器设计

为实现对自由翻滚的失控目标航天器进行在轨服务,基于二阶滑模控制算法设计了相对位置与姿态耦合的自适应控制器。考虑相对转动对相对平动的耦合作用,建立了两航天器对接端口间相对位置与姿态耦合的动力学模型,并在此基础上设计了自适应Super twisting控制器,以减弱已知界限的有界干扰所产生的震颤效应,使闭环系统在有限时间内收敛到平衡点。利用李雅普诺夫方法证明了有界干扰下的闭环系统稳定性,并对收敛时间的上界进行了估计。仿真结果表明,与Super twisting算法相比,所设计的自适应二阶滑模控制器对参数不确定性及线性增长有界干扰具有较强的鲁棒性,且控制精度满足在轨服务的任务需求。     

相对失控翻滚目标悬停的自适应模糊滑模控制

研究了含有系统不确定性和外部干扰的追踪器相对失控翻滚目标悬停的六自由度耦合控制问题。首先，在追踪器本体坐标系中建立了非线性的六自由度耦合的一体化动力学模型，将悬停控制问题转化为相对位置和相对姿态控制问题。再基于模糊逼近原理设计了一种自适应的模糊滑模控制器，该控制器能够有效克服系统的模型不确定性和外部干扰的影响，并能消除传统的抖振问题。由Lyapunov方法导出了模糊自适应律并证明了闭环系统的稳定性。数值仿真验证了所提的自适应模糊滑模控制器的有效性。     

新型快速Terminal滑模及其在近空间飞行器上的应用

为加快Terminal滑模收敛速度,并避免控制器奇异,首先分析了Terminal滑模产生奇异的原因,基于李代数给出Terminal滑模控制器非奇异判据.然后,设计了两种新型非奇异快速Terminal滑模,其收敛速度在任意点均快于现有标准快速Terminal滑模;给出了收敛时间公式.将新型快速Terminal滑模与动态滑...     

Robust formation control for missiles with obstacle avoidance

This paper investigates the robust formation control for missiles with obstacle avoidance.A sliding mode surface that is asymptotically stable is firstly presented by the collision avoidance potential function and hyperbolic tangent function. Based on the sliding mode surface, a robust formation controller with obstacle avoidance is designed for missiles. To improve the convergence rate,a finite-time controller which can deal with the formation control for missiles is given using an improved sli...     

基于非奇异快速终端滑模的永磁同步电机转速和电流控制

针对永磁同步电机在矢量控制中存在转速和电流频繁超调、稳态精度低、鲁棒性弱等问题,运用非奇异快速终端滑模控制器替代传统PI控制下的转速环控制器和电流环控制器,并采用李雅普诺夫函数证明了3个控制器的稳定性。借助MATLAB/Simulink仿真软件分析了采用非奇异快速终端滑模控制器和PI控制器的转速、电流响应波形。仿真结果表明:采用非奇异快速终端滑模控制器有更小的超调量、更高的稳态精度和更强的鲁棒性。     

基于反演设计的无人水下航行器自适应二阶滑模控制

针对存在参数不确定性和结构不确定性的无人水下航行器,利用反演设计方法设计了无人水下航行器的控制器,并利用自适应控制方法在线估计参数变化率。同时,结合滑模控制克服系统中的未建模动态特性；比较了传统滑模控制与二阶滑模控制的区别,充分体现二阶滑模控制对传统滑模控制中颤振的削弱作用；仿真验证了设将反演设计与自适应控制、滑模变结构控制相结合,.x性的系统,且非线性参数不确定,在这种情况下需要.x 计方法的有效性和正确性。     

Adaptive recurrent-neural-network control for linear inductionmotor

In this study an adaptive recurrent-neural-network controller (ARNNC) is proposed to control a linear induction motor (LIM) servo drive. First, the secondary flux of the LIM is estimated with an adaptive flux observer on the stationary reference frame and the feedback linearization theory is used to decouple the thrust force and the flux amplitude of the LIM. Then, an ARNNC is proposed to control the mover of the LIM for periodic motion. In the proposed controller, the LIM servo drive system is identified by a recurrent-neural-network identifier (RNNI) to provide the sensitivity information of the drive system to an adaptive controller. The backpropagation algorithm is used to train the RNNI on line. Moreover, to guarantee the convergence of identification and tracking errors, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the RNNI and the optimal learning rate of the adaptive controller. The effectiveness of the proposed control scheme is verified by both the simulated and experimental results. Furthermore, the advantages of the proposed control system are indicated in comparison with the sliding mode control system     

机械手的神经网络自适应滑动模控制器设计

 针对多关节机械手的鲁棒跟随控制器设计问题，提出了一种新的机械手神经网络自适应滑动模控制器设计方法，机械手的动力学非线性假设是完全未知的。在提出的控制结构中，高斯径向基函数神经网络用于在线补偿机械手的动力学非线性，参数学习律由稳定性理论得到。给出了系统稳定性和参数收敛性的证明。最后提出方法的可行性通过仿真得到验证。     

Observer-based adaptive sliding mode backstepping output-feedback DSC for spin-stabilized canard-controlled projectiles

This article presents a complete nonlinear controller design for a class of spin-stabilized canard-controlled projectiles.Uniformly ultimate boundedness and tracking are achieved,exploiting a heavily coupled,bounded uncertain and highly nonlinear model of longitudinal and lateral dynamics.In order to estimate unmeasurable states,an observer is proposed for an augmented multiple-input-multiple-output(MIMO) nonlinear system with an adaptive sliding mode term against the disturbances.Under the frame of a backstepping design,an adaptive sliding mode output-feedback dynamic surface control(DSC) approach is derived recursively by virtue of the estimated states.The DSC technique is adopted to overcome the problem of ‘‘explosion of complexity" and relieve the stress of the guidance loop.It is proven that all signals of the MIMO closed-loop system,including the observer and controller,are uniformly ultimately bounded,and the tracking errors converge to an arbitrarily small neighborhood of the origin.Simulation results for the observer and controller are provided to illustrate the feasibility and effectiveness of the proposed approach.     

Adaptive Integral-type Sliding Mode Control for Spacecraft Attitude Maneuvering Under Actuator Stuck Failures

A fault tolerant control (FTC) design technique against actuator stuck faults is investigated using integral-type sliding mode control (ISMC) with application to spacecraft attitude maneuvering control system. The principle of the proposed FTC scheme is to design an integral-type sliding mode attitude controller using on-line parameter adaptive updating law to compensate for the effects of stuck actuators. This adaptive law also provides both the estimates of the system parameters and external disturbances such that a prior knowledge of the spacecraft inertia or boundedness of disturbances is not required. Moreover, by including the integral feedback term, the designed controller can not only tolerate actuator stuck faults, but also compensate the disturbances with constant components. For the synthesis of controller, the fault time, patterns and values are unknown in advance, as motivated from a practical spacecraft control application. Complete stability and performance analysis are presented and illustrative simulation results of application to a spacecraft show that high precise attitude control with zero steady-error is successfully achieved using various scenarios of stuck failures in actuators.     

Adaptive control for feedback-linearized missiles withuncertainties

A robust adaptive control scheme is proposed that can be applied to a practical autopilot design for feedback-linearized skid-to-turn (STT) missiles with aerodynamic uncertainties. The approach is to add a robust adaptive controller to a feedback-linearizing controller in order to reduce the influence of the aerodynamic uncertainties. The proposed robust adaptive control scheme is based on a sliding mode control technique with an adaptive law for estimating the unknown upper bounds of uncertain parameters. A feature of the proposed scheme is that missile systems with aerodynamic uncertainties can be controlled effectively over a wide operating range of flight conditions. It is shown, using Lyapunov stability theory, that the proposed scheme can give sufficient tracking capability and stability for a feedback-linearized STT missile with aerodynamic uncertainties. The six-degree-of-freedom nonlinear simulation results also show that good performance for several uncertainty models and engagement scenarios can be achieved by the proposed scheme in practical night conditions     

基于神经网络的双馈感应发电机滑模控制

针对不平衡电网下双馈感应发电机运行不佳的问题,将神经网络控制和二阶滑模控制相结合构成的神经网络滑模控制器运用到双馈风力发电机的直接功率控制中。设计了二阶滑模控制器,二阶滑模能够有效地削弱传统滑模控制的抖振；接着,设计了径向基神经网络对系统的不确定部分进行逼近；最后,基于李雅普诺夫稳定性定理推导了神经网络权值更新律,证明了控制系统的稳定性。仿真结果表明所设计控制策略能对有功、无功功率及其定子电流进行有效控制,削弱了传统滑模控制中的抖振。