Adaptive fault-tolerant controller design for airbreathing hypersonic vehicle with input saturation

The problem of fault-tolerant control is discussed for the longitudinal model of an airbreathing hypersonic vehicle （AHV） with actuator faults and external disturbances. Firstly, a fault-tolerant control strategy is presented for the longitudinal model of an AHV, which guarantees that velocity and altitude track their reference trajectories at an exponential convergence rate. However, this method needs to know the minimum value of the actuator efficiency factor and the upper bound of the external disturbances, which makes it not easy to implement. Then an improved adaptive fault-tolerant control scheme is proposed, where two adaptive laws are employed to estimate the upper bound of the external disturbances and the minimum value of the actuator efficiency factor, respectively. Secondly, the problem of designing a control scheme with control constraints is further considered, and a new adaptive fault-tolerant control strategy with input saturation is designed to guarantee that velocity and altitude track their reference trajectories. Finally, simulation results are given to show the effectiveness of the proposed methods.

Robust adaptive control of hypersonic vehicle considering inlet unstart

In this paper,a model reference adaptive control(MRAC)augmentation method of a linear controller is proposed for air-breathing hypersonic vehicle(AHV)during inlet unstart.With the development of hypersonic flight technology,hypersonic vehicles have been gradually moving to the stage of weaponization.During the maneuvers,changes of attitude,Mach number and the back pressure can cause the inlet unstart phenomenon of scramjet.Inlet unstart causes significant changes in the aerodynamics of AHV,which may lead to deterioration of the tracking performance or instability of the control system.Therefore,we firstly establish the model of hypersonic vehicle considering inlet unstart,in which the changes of aerodynamics caused by inlet unstart is described as nonlinear uncertainty.Then,an MRAC augmentation method of a linear controller is proposed and the radial basis function(RBF)neural network is used to schedule the adaptive parameters of MRAC.Furthermore,the Lyapunov function is constructed to prove the stability of the proposed method.Finally,numerical simulations show that compared with the linear control method,the proposed method can stabilize the attitude of the hypersonic vehicle more quickly after the inlet unstart,which provides favorable conditions for inlet restart,thus verifying the effectiveness of the augmentation method proposed in the paper.

Flight control for air-breathing hypersonic vehicles using linear quadratic regulator design based on stochastic robustness analysis

The flight dynamics model of air-breathing hypersonic vehicles （AHVs） is highly nonlinear and multivariable cou- pling, and includes inertial uncertainties and external disturbances that require strong, robust, and high-accuracy controllers. In this paper, we propose a linear-quadratic regulator （LQR） design method based on stochastic robustness analysis for the longitudinal dynamics of AHVs. First, input/output feedback linearization is used to design LQRs. Second, subject to various system parameter uncertainties, system robustness is characterized by the probability of stability and desired performance. Then, the mapping rela- tionship between system robustness and LQR parameters is established. Particularly, to maximize system robustness, a novel hybrid particle swarm optimization algorithm is proposed to search for the optimal LQR parameters. During the search iteration, a Chernoff bound algorithm is applied to determine the finite sample size of Monte Carlo evaluation with the given prohabilily levels. Finally, simulation results show that the optimization algorithm can effectively find the optimal solution to the LQR parameters.

吸气式高超声速飞行器控制的最新研究进展

随着超燃冲压发动机技术的快速发展,吸气式高超声速飞行器正受到世界范围内的高度关注,而其控制系统的设计则是重中之重.首先简要回顾了吸气式高超声速飞行器建模的发展,表明了对其进行控制器设计的复杂性;然后着重阐述了几种广泛应用于吸气式高超声速飞行器的控制方法:基于线性化模型的控制方法、反向递推法、T-S模糊控制方法、自适应控制和滑模变结构控制;最后指出了在控制器设计环节需要考虑的若干问题,例如:执行机构的非线性、容错控制、多目标控制、切换控制等,同时也是今后吸气式高超声速飞行器控制系统设计的研究方向.

考虑动压限制的高超声速飞行器控制系统设计

针对高超声速飞行器超燃冲压发动机的进气道对飞行动压有比较苛刻的要求,提出一种直接进行动压反馈的高超声速飞行器控制系统设计方法。首先,建立了高超声速飞行器动压反馈控制的动力学模型,并推导了动压控制的状态方程。然后,利用线性二次型最优控制方法,通过引入动压误差进行控制对象增广,从而在动压控制回路中引入积分控制,以消除动压跟踪误差,给出了高超声速飞行器动压控制的控制系统结构。最后,通过仿真验证了动压控制器具有很好的跟踪性能,考虑存在气动、推力不确定性因素,飞行器速度出现偏差时,动压控制系统可以自适应地调整飞行高度以保证对动压指令的跟踪,控制系统具有很好的鲁棒性。

考虑进气道不起动的高超声速飞行器鲁棒自适应控制研究

针对吸气式高超声速飞行器进气道不起动引起飞行器气动特性大范围变化,从而导致响应出现大幅振荡甚至控制系统失稳的问题,提出了一种考虑进气道不起动影响的模型参考自适应控制方法。该方法首先针对进气道起动时的模型,设计了基于LQR-PI方法的姿态控制系统,并以此作为进气道不起动时的参考模型;当进气道不起动时,在LQR-PI基准控制器的基础上增加模型参考自适应控制项,通过跟踪参考模型以提高系统对进气道不起动引起模型偏差的鲁棒性,在进气道出现不起动的情况下能快速稳定姿态,为进气道再起动提供条件。最后对所提方法进行了数字仿真,结果表明,系统在进气道出现不起动时能够快速跟踪控制指令,且稳态误差趋于零,验证了所提方法的有效性。

状态/输入约束下飞-推一体化的保性能安全控制

基于飞行-推力一体化思想提出了一种针对搭载超燃冲压发动机的吸气式高超声速飞行器速度通道的状态/输入约束自适应鲁棒保性能安全控制方案。首先根据超燃冲压发动机的机理分析与计算流体动力模型数据,建立了安全子系统与性能子系统面向控制的仿射非线性模型。之后基于障碍Lyapunov理论与动态面设计方法设计了一套安全子系统状态约束控制器,从理论上保证了飞行器在跟踪指令的全过程中,发动机相关状态不会触碰安全边界,并结合自适应技术与辅助系统提高了该控制系统的鲁棒性。针对性能子系统设计了一套鲁棒自抗扰控制器,达到“保证安全的前提下不折损性能”的目的。仿真结果表明所设计的控制系统可以在保障安全的同时达到预想的性能,并显著放宽了超燃冲压发动机对飞行器飞行姿态的约束,保证了高超声速飞行器的机动灵活性。

变几何进气道吸气式高超声速飞行器控制系统设计

建立了变几何进气道吸气式高超声速飞行器(AHV-VGI)的纵向模型。针对纵向模型中由于参数拟合以及可移动唇罩引入的不确定性、飞行器所受不确定外来干扰,提出了一种基于模糊干扰观测器的AHV-VGI动态面控制方案。仿真结果表明:所提方法能够对AHV-VGI系统进行有效控制,相对于传统的定几何进气道(FGI) AHV(AHV-FGI)的控制,性能更优。

基于时延的高超声速飞行器终端滑模控制

针对吸气式高超声速飞行器(AHV)再入过程中的复杂非线性、动力学模型通道间存在的强耦合及气动力系数和气动力矩系数摄动,提出了一种结合时延补偿控制与终端滑模控制的姿态控制方法.首先,以AHV再入飞行姿态动力学模型为基础,考虑气动参数摄动产生的模型不确定性,建立了面向控制算法设计的AHV再入飞行数学模型;然后,基于多时间尺度理论将该数学模型分解为双环子系统;为两个子系统分别设计时延补偿改进终端滑模控制算法,用来完成AHV的再入姿态控制;在改进终端滑模控制的基础上,采用工程上易于实现的时延补偿控制对模型不确定性进行精确估计,并基于李雅普诺夫理论证明了姿态角和姿态角速度的跟踪误差在有限时间内收敛到零.本算法设计简单,无须补偿项部分已知且易于工程实现.仿真结果表明所设计的基于时延补偿的改进控制算法具有调整时间短(1 s以内)、超调量小和良好的跟踪精度等优点.