基于Terminal 滑模的高超声速飞行器姿态控制

针对高超声速飞行器六自由度再入模型,考虑模型参数不确定和外界干扰对再入姿态控制的影响,基于Terminal滑模对再入过程中姿态角的跟踪控制问题进行研究.为了减少外界高频噪声对系统性能的影响,首先,利用多时间尺度技术将姿态模型划分为双环结构;然后,分别针对各环路设计Terminal滑模控制器,并通过Lyapunov理论和奇异摄动理论对系统的稳定性进行证明.仿真结果表明,对于六自由度再入模型,该控制方法能够很好地跟踪再入制导指令.     

高超声速飞行器姿态的变结构控制

针对高超声速飞行器运行环境中气动参数大范围变化可能导致失稳现象,构建高超声速飞行器姿态的滑模变结构控制器。通过多时间尺度理论将飞行器姿态控制系统分为内外双闭环子系统,分别为内外环设计滑模姿态控制律,保证控制系统对气动参数变化不敏感,能稳定准确地跟踪期望姿态角指令。仿真结果表明所提滑模变结构姿态控制算法性能良好,对气动参数变化有一定的鲁棒性。     

基于拟连续高阶滑模的高超声速飞行器再入姿态控制

考虑模型参数不确定和外界干扰对再入制导控制性能的影响,基于拟连续高阶滑模控制策略对高超声速飞行器的再入制导控制问题进行了研究.首先,给出再入制导指令的设计过程.其次,基于再入飞行特性对模型进行简化,获得面向控制的姿态模型,在此基础上,通过引入新的控制变量,设计解耦滑模面,实现姿态间的解耦.再次,为了削弱控制抖振,通过引入虚拟控制,对系统进行增广,基于齐次性理论设计拟连续三阶滑模再入姿态控制器,确保系统在有限时间实现对制导指令的稳定跟踪.最后,六自由度再入飞行器的制导控制一体化仿真结果表明,本研究给出的控制策略在不影响系统鲁棒性的同时,能够实现对标称轨迹和再入姿态的综合控制.     

基于sigmoid函数的高超声速飞行器自适应姿态控制

针对高超声速飞行器无动力再入过程中具有强耦合、气动参数摄动及不确定性的非线性姿态模型,提出了飞行器姿态控制的一种非线性设计方法。首先基于时标分离原理分内外环设计非线性动态逆控制器,并利用Sigmoid函数分通道制定控制律。针对单纯使用动态逆控制鲁棒性弱的特点,引入基于扩张状态观测器(Extended State Observer,ESO)的自适应控制器对参数摄动和不确定性进行补偿,在参数拉偏和风干扰条件下仿真结果验证了设计控制器具有较强的鲁棒性。     

基于模型参考的高超声速飞行器自适应滑模控制

针对高超声速飞行器过渡段的姿态控制问题,提出一种基于模型跟踪的自适应滑模直接力/气动力复合控制方法;该方法选择法向过载和俯仰角速率作为状态变量,实现了系统全状态反馈,在滑模控制中通过引入自适应机制克服吸气式冲压发动机不同工作状态引起的被控模型参数不确定性,利用Lyapunov理论证明了闭环系统全局渐近稳定性;不同条件下仿真结果表明,所设计方法对攻角指令有较好的跟踪效果,对模型不确定性具有较好的鲁棒性.     

高超声速飞行器姿态控制系统设计

研究气动特性是飞行器姿态稳定性的保证,高超声速飞行器采用姿态控制有助于提高作战效能及生存能力.针对高超声速飞行器作战环境复杂,大气密度偏差大、力/力矩系数不准确造成气动参数偏差较大等特点,采用参数空间方法来设计姿态控制系统.首先建立适用于姿态控制系统的高超声速数学模型,在高超声速气动特性条件下,提出三回路姿态稳定控制系统,根据参数空间方法的原理设计出各回路控制器,最后进行仿真分析验证控制系统的性能.仿真结果表明当气动参数存在较大偏差时,采用基于参数空间法设计的高超声速姿态控制系统可以确保对指令的精确跟踪,并且具有较强的鲁棒稳定性.     

基于神经网络补偿的高超声速飞行器滑模控制

针对吸气式高超声速飞行器的轨迹控制问题,提出了一种基于自适应径向基函数(RBF)神经网络的滑模控制方法.建立了高超声速飞行器的纵向动态模型;设计了滑模控制器,利用自适应RBF神经网络对系统不确定项进行在线逼近,对滑模控制器进行补偿;基于李雅普诺夫的稳定性分析证明了闭环系统的稳定性.仿真结果表明:控制系统能够实现对于高超声速飞行器给定指令的有效跟踪.     

高超声速飞行器飞行轨迹的模糊控制设计

针对高超声速飞行器飞行过程中因干扰造成的飞行轨迹散布问题,提出了采用飞行器飞行轨迹的模糊控制设计方法。方法以高超声速飞行器飞行轨迹线偏差和线偏差变化率作为模糊控制器输入,采用模糊推理设计飞行控制系统。在完成高超声速飞行轨迹控制系统数学建模的基础上,结合自动驾驶仪特点对飞行轨迹模糊控制系统进行了设计。结论通过仿真表明所设计的飞行控制系统满足飞行轨迹及攻角性能要求,验证了方法的正确性。     

高超声速飞行器神经网络动态逆姿态控制器设计

以一类通用高超声速飞行器纵向模型为研究对象,推导了飞行器纵向姿态运动方程。考虑受到飞行器附加攻角扰动以及气动参数不确定性的影响,对运动方程中速率变化快慢不同的攻角和俯仰速率分别引入精确线性化动态逆反馈,并利用神经网络对系统逆反馈误差进行补偿,有效地抑制了模型参数摄动,实现了对攻角指令的精确跟踪。将设计的控制器对高超声速非线性模型进行系统闭环仿真,仿真结果说明所设计的姿态控制器具有抗参数摄动的性能,能够满足高超声速飞行器复杂飞行条件下的姿态控制要求,具有较强的鲁棒性。     

高超声速飞行器轨迹跟踪的反步滑模控制

针对高超声速飞行器轨迹跟踪控制问题,基于纵向动力学的输入/输出线性化模型,设计了一种基于反步法与滑模控制相结合的反步滑模跟踪控制器;这种控制器对系统匹配不确定性和非匹配不确定性都具有较强的鲁棒性,跟踪收敛快速性良好;对反步滑模跟踪控制器和一般滑模跟踪控制器进行了控制参数仿真优化,对比研究了速度跟踪、高度跟踪、速度高度同时跟踪和正弦速度跟踪条件下两种控制器的快速性和鲁棒性,证实了文章方法的有效性。     

Second-order terminal sliding mode control for hypersonic vehicle in cruising flight with sliding mode disturbance observer

This paper focuses on the design of nonlinear robust controller and disturbance observer for the longitudinal dynamics of a hypersonic vehicle (HSV) in the presence of parameter uncertainties and external disturbances. First, by combining terminal sliding mode control (TSMC) and second-order sliding mode control (SOSMC) approach, the secondorder terminal sliding control (2TSMC) is proposed for the velocity and altitude tracking control of the HSV. The 2TSMC possesses the merits of both TSMC and SOSMC, which can provide fast convergence, continuous control law and hightracking precision. Then, in order to increase the robustness of the control system and improve the control performance, the sliding mode disturbance observer (SMDO) is presented. The closed-loop stability is analyzed using the Lyapunov technique. Finally, simulation results illustrate the effectiveness of the proposed method, as well as the improved overall performance over the conventional sliding mode control (SMC).     

Neural network based adaptive fuzzy PID-type sliding mode attitude control for a reentry vehicle

This work investigates the attitude control of reentry vehicle under modeling inaccuracies and external disturbances. A robust adaptive fuzzy PID-type sliding mode control (AFPID-SMC) is designed with the utilization of radial basis function (RBF) neural network. In order to improve the transient performance and ensure small steady state tracking error, the gain parameters of PID-type sliding mode manifold are adjusted online by using adaptive fuzzy logic system (FLS). Additionally, the designed new adaptive law can ensure that the closed-loop system is asymptotically stable. Meanwhile, the problem of the actuator saturation, caused by integral term of sliding mode manifold, is avoided even under large initial tracking error. Furthermore, to eliminate the need of a priori knowledge of the disturbance upper bound, RBF neural network observer is used to estimate the disturbance information. The stability of the closed-loop system is proved via Lyapunov direct approach. Finally, the numerical simulations verify that the proposed controller is better than conventional PID-type SMC in terms of improving the transient performance and robustness.

     

带有干扰观测器的高超声速飞行器滑模控制

针对高超声速飞行器非线性和易受干扰影响的特点,提出了带有扩张状态干扰观测器的连续滑模控制方法.在对飞行器非线性模型做线性化处理的基础上,设计了一种连续时间滑模控制器.该控制器在对不确定性和未知动态保持鲁棒性的基础上,消除了传统滑模中存在的抖振现象.对系统中存在的外加干扰,设计了扩张状态干扰观测器.将外加干扰作为系统的一个状态变量被估计出来,再将估计值用作滑模控制器的补偿量,进而达到消除外干扰的目的.在高超声速飞行器巡航飞行状态的基础上进行了仿真.仿真结果表明,所提出的方案能够满足控制要求.     

Novel smooth sliding mode attitude control design for constrained re-entry vehicle based on disturbance observer

This paper investigates the attitude tracking control system design for reusable launch vehicle (RLV) in re-entry phase with input constraint, model uncertainty and external disturbance. The novel control scheme is designed via combining the advantages of the robust property of sliding mode control (SMC), the compensation ability of disturbance observer (DOB) and the systematic design procedure of backstepping technique. By applying DOB technique to estimate the lumped uncertainty, there is no need to choose the switch gain larger than the bound of uncertainty. Through designing the exponential form sliding surface and smooth sliding mode controller, the chattering and discontinuous problem inherent in the traditional SMC is alleviated. An additional system is constructed to handle input constraint. Based on Lyapunov theory, the asymptotic stability of the closed-loop system is proven. At last, compared simulations are presented to verify the effectiveness of the proposed control approach.     

基于高阶滑模观测器的自适应时变滑模再入姿态控制

针对再入飞行器鲁棒姿态控制问题, 提出一种基于高阶滑模观测器的自适应时变滑模控制器设计方法. 首先, 设计了一种时变滑模面, 并在此基础上推导了相应的时变滑模控制律, 其中滑模控制中切换增益通过一种自适应算法获得, 消除了控制器设计过程中对系统不确定性上界已知的要求; 然后, 利用高阶滑模观测器对控制器设计过程中用到的姿态角导数信息进行观测, 同时能够获得系统扰动估计值, 从而构造一种基于观测器的控制器形式; 最后, 通过仿真验证了所提出的控制算法在提高再入飞行器姿态控制精度以及系统鲁棒性方面的有效性.     

Second-order sliding mode control with backstepping for aeroelastic systems based on finite-time technique

In this paper, a backstepping second-order sliding mode control scheme (BSOSMC) is proposed for suppressing both flutter and limit cycle oscillation in the aeroelastic system. The proposed control scheme combining the sliding mode control and backstepping technique, which obtain the properties of fast response and improve the control accuracy. To obtain a better disturbance rejection property, we employ compensated control term. The compensated control term provides the complete compensation of the uncertainty and disturbance, and it relax the requirement of the bound of uncertainty and disturbance. The convergence and stability of the proposed control scheme are proved by using Lyapunov’s method. Finally, the simulation results demonstrate the effectiveness of the proposed control scheme.     

Direct parametric attitude tracking control for generic hypersonic vehicle

This paper considers the attitude tracking problem for the generic hypersonic vehicle (GHV). First, the second-order nonlinear GHV attitude model is introduced. Second, by utilising the direct parametric approach, a modified parametric controller composed of the parametric state proportional plus derivative feedback controller and the feedforward controller is proposed. With application of the first part, the closed-loop system is a constant linear system with desired eigenstructures, and the second part is used to ensure the asymptotic tracking property of the outputs of the GHV attitude system. Since the control input of the established GHV attitude model is moment command, an algorithm that transforms the moment commands into the fins deflection command is proposed. Finally, the effectiveness of the proposed parametric controller and transform algorithm is illustrated by the numerical simulation results.