Reference tracking control for flexible air-breathing hypersonic vehicle with actuator delay and uncertainty

This paper considers the problem of reference tracking control for the flexible air-breathing hypersonic flight vehicle with actuator delay and uncertainty.By constructing the Lyapunov functional including the lower and upper bounds of the time-varying delay,the non-fragile controller is designed such that the resulting closed-loop system is asymptotically stable and satisfies a prescribed performance cost index.The simulation results are given to show the effectiveness of the proposed control method,which is validated by excellent output reference altitude and velocity tracking performance.     

Polytopic LPV modeling and gain-scheduled switching control for a flexible air-breathing hypersonic vehicle

A novel gain-scheduled switching control method for the longitudinal motion of a flexible air-breathing hypersonic vehicle (FAHV) is proposed.Firstly,velocity and altitude are selected as scheduling variables,a polytopic linear parameter varying(LPV) model is developed to represent the complex nonlinear longitudinal dynamics of the FAHV.Secondly,based on the obtained polytopic LPV model,the flight envelope is divided into four smaller subregions, and four gain-scheduled controllers are designed for these parameter subregions.Then,by the defined switching characteristic function,these gain-scheduled controllers are switched in order to guarantee the closed-loop FAHV system to be asymptotically stable and satisfy a given tracking error performance criterion.The condition of gain-scheduled switching controller synthesis is given in terms of linear matrix inequalities(LMIs) which can be easily solved by using standard software packages.Finally,simulation results show the effectiveness of the presented method.     

Adaptive dynamic surface control for air-breathing hypersonic vehicle

This paper describes an adaptive control approach for an air-breathing hypersonic vehicle.The control objective is to provide robust altitudes and velocity tracking in the presence of model uncertainties and varying disturbances.A fuzzy-neural disturbance observer is developed to estimate uncertainties and disturbances,and the adaptive controller is synthesized by the dynamic surface approach combing with the observer.The tracking error at the steady state can be guaranteed to converge to inside of a small residue set which the size of the set can be an arbitrary small value.Simulation results demonstrate the effectiveness of the presented approach.     

Flight control for a flexible air-breathing hypersonic vehicle based on quasi-continuous high-order sliding mode

The focus of this paper is on control design and simulation for the longitudinal model of a flexible air-breathing hypersonic vehicle(FAHV).The model of interest includes flexibility effects and intricate couplings between the engine dynamics and flight dynamics.To overcome the analytical intractability of this model,a nominal control-oriented model is constructed for the purpose of feedback control design in the first place.Secondly,the multi-input multi-output(MIMO) quasi-continuous high-order sliding mode(HOSM) controller is proposed to track step changes in velocity and altitude,which is based on full state feedback.The simulation results are presented to verify the effectiveness of the proposed control strategy.     

弹性高超声速飞行器智能控制系统设计

针对气动舵受限下的弹性高超声速飞行器控制问题, 提出一种基于神经自适应的智能控制方案。在速度子系统的设计过程中, 为了降低对模型参数的依赖程度, 应用强化学习算法在线调整比例积分微分(proportional integral derivative, PID)控制参数, 给出智能PID控制策略。对于高度子系统, 考虑气动舵的动态特性, 利用神经自适应方法对模型未知函数及不确定项进行逼近。为了处理气动舵的约束问题, 以非线性模型预测控制为优化分配模板生成大量样本数据集, 经离线训练得到深度神经网络代替求解复杂优化问题和控制分配的过程。此外, 通过引入自适应超螺旋微分器处理外部扰动, 增强了系统的鲁棒性。利用Lyapunov方法证明了所设计控制器的稳定性, 并通过仿真验证了所设计控制方案能够快速计算控制指令, 实现高精度跟踪控制。     

高超声速伸缩式变形飞行器再入轨迹快速优化

针对高超声速变形飞行器再入轨迹优化问题,研究了一种基于改进高斯伪谱法(Gauss pseudospectral method,GPM)的快速优化方法.首先,针对一种采用伸缩式机翼的高超声速变形飞行器,建立了将展长变形量扩展成为控制变量的再入轨迹优化模型.其次,采用GPM将轨迹优化问题转化为非线性规划(nonlinear...     

奇异时滞系统的鲁棒故障检测和分离观测器

讨论了一类不确定奇异时滞系统的鲁棒故障检测和分离观测器(RDO)设计问题,设计所有的观测器使得它们的冗余信号对非故障因素具有鲁棒性,并设计每个观测器使其冗余信号对一组特定的故障不敏感而对其余故障敏感。给出了RDO存在的充分条件及有效的设计算法,并讨论了故障集合不同划分的RDO设计之间的关系,最后给出一具体算例来说明该方法的有效性。     

高超声速飞行器自抗扰姿态控制器设计

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,结合自抗扰控制中的扩张状态观测器(extended state observer, ESO)及非线性状态误差反馈律(nonlinear law state error feedback, NLSEF),分别设计了高超声速飞行器内环和外环自抗扰姿态控制器。将不确定性、耦合及参数摄动等干扰作为“总和干扰”利用扩张状态观测器进行估计并动态反馈补偿,再利用NLSEF抑制补偿残差。自抗扰控制器(active disturbance rejection control, ADRC)设计无需精确的飞行器被控模型,也无需精确的气动参数及摄动界限。仿真结果表明,控制系统能够克服干扰及气动参数大范围摄动的影响,在获取良好的动态品质和跟踪性能的同时,具有较强的鲁棒性。     

Progress in reentry trajectory planning for hypersonic vehicle

The reentry trajectory planning for hypersonic vehicles is critical and challenging in the presence of numerous nonlinear equations of motion and path constraints, as well as guaranteed satisfaction of accuracy in meeting all the specified boundary conditions. In the last ten years, many researchers have investigated various strategies to generate a feasible or optimal constrained reentry trajectory for hypersonic vehicles. This paper briefly reviews the new research efforts to promote the capability of reentry trajectory planning. The progress of the onboard reentry trajectory planning, reentry trajectory optimization, and landing footprint is summarized. The main challenges of reentry trajectory planning for hypersonic vehicles are analyzed, focusing on the rapid reentry trajectory optimization, complex geographic constraints, and coop- erative strategies.     

基于多智能体导航的高超飞行器信息融合方法

精确导航技术是高超飞行器(hypersonic vehicle, HV)充分发挥威力的关键所在。然而,高马赫数和强机动性致使HV的导航系统误差及其观测噪声无法准确描述,制约着导航信息的精确性和实时性。为及时获取高精度导航信息,设计基于集员框架的卡尔曼滤波算法。一方面采用多智能体分布式协同探测,形成观测椭球交叉集合,提高了观测效率和测量精度;另一方面,通过设计两类噪声模型,求其与状态估值的最小均方误差,实现滤波增益的计算,提高算法对噪声的抗扰动能力,使状态估值达到均方误差最小。通过数字仿真,将设计方法应用到HV导航模型中,并与扩展卡尔曼滤波和集员滤波的状态估值进行比较,结果表明,提出算法在不同噪声影响下具有更高的估计精度。研究成果将为HV实现实时精确导航提供技术支持,并具有重要的理论意义和应用价值。     

弹性高超声速飞行器动态面制导控制一体化设计方法

面向弹性高超声速飞行器滑翔段制导控制系统设计问题,应用动态面控制理论设计了两种制导控制一体化方法.建立了弹性高超声速飞行器滑翔段纵向运动模型,并推导了具有严格反馈形式的弹性高超声速飞行器制导控制一体化设计模型.将弹性状态视为不确定项,分别基于自适应方法和非线性干扰观测器(nonlinear disturbance ob...     

基于神经网络的高超声速飞行器惯导系统精度提高方法

针对目前惯性系统误差补偿模型对静态误差和动态误差处理能力不足的问题,为适应高超声速飞行器长航时、高精度的惯性导航要求,基于神经网络提出一种加速度计拟合模型。在高超声速飞行器飞行前期有准确的卫星导航信息时,收集导航信息和加速度计脉冲信息,利用神经网络强大的非线性拟合能力,在飞行过程中进行在线训练,得到精确的惯性系统模型。仿真结果表明,在存在逐次通电误差和不考虑二次项误差系数的误差补偿模型方法位置导航偏差在数公里和数百米量级的情况下,相同时间内所提方法的位置导航偏差仅为数十米量级,有效提高了高超声速飞行器的导航精度。     

高超声速飞行器新型攻角约束反演控制

针对考虑攻角约束的高超声速飞行器控制问题,提出一种受限指令滤波器与预设性能方法相结合的反演控制方案.首先,从高超声速飞行器运动模型中划分出高度子系统并基于反演控制方法设计控制器.为了解决攻角约束问题,构造受限指令滤波器对攻角虚拟指令限幅并保证指令的可导性.然后,利用预设性能方法预先设定约束范围,保证攻角跟踪误差始终满足...     

Diagnosis of process faults and sensor faults in a class of nonlinear uncertain systems

This paper presents a fault diagnosis method for process faults and sensor faults in a class of nonlinear uncertain systems.The fault detection and isolation architecture consists of a fault detection estimator and a bank of adaptive isolation estimators,each corresponding to a particular fault type.Adaptive thresholds for fault detection and isolation are presented.Fault detectability conditions characterizing the class of process faults and sensor faults that are detectable by the presented method are derived.A simulation example of robotic arm is used to illustrate the effectiveness of the fault diagnosis method.     

基于系统异常概率模型的故障分离自动化方法

研究了发动机状态参数异常对发动机整体性能的影响,利用多元统计分析方法建立了状态变量对发动机性能影响的概率模型,用于发动机性能监控过程中的故障分离。根据模型能够计算出发动机性能出现异常时各个状态变量导致此时刻性能异常的概率,据此初步判断哪些状态变量导致发动机性能出现异常,并根据概率的大小对相应部件进行检查,以此来寻找故障源。在某型涡扇发动机性能监控中的应用表明,通过计算异常样本点上各监测参数对样本点异常的影响概率,并结合发动机故障机理分析,能够有效地确定故障源。     

基于RCMAC干扰观测器的高超声速飞行控制

利用自回归小脑模型神经网络(recurrent cerebella model neural network, RCMAC)良好的非线性逼近能力和自学习能力,结合反馈线性化和反演控制方法,提出了一种自适应非线性控制策略,用于高速再入飞行器控制系统的设计。该方案将RCMAC干扰观测器(recurrent cerebella disturbance observer, RCDO)用于估计系统模型的不确定项,同时采用反演控制方式设计伪线性控制项,并利用符号函数逼近误差的上界,根据Lyapunov稳定性理论设计了权值更新规则,保证闭环系统信号有界。高速再入飞行器的六自由度仿真结果验证了方法的有效性和鲁棒性。     

ToMFIR-based fault detection approach in frequency domain

This paper is to explore further results for total measurable fault information-based residual (ToMFIR) approach to fault detection in dynamic systems. The ToMFIR contains the essential fault information and remains unaffected by control actions in a closed-loop system. It is composed of controller residual and output residual and some of further results are developed in frequency domain. Besides the ability of detecting actuator and sensor faults, it is able to detect faults/failures resulting from the computer used for control purpose that generates control signals. Currently, all of existing fault detection schemes cannot achieve the same task at all. A practical DC motor example, with a PID controller, is used to demonstrate the effectiveness of the ToMFIR-based fault detection. A comparison with the standard observer-based technique is also provided.     

控制系统故障检测与诊断技术的最新进展

对故障检测与诊断(FDD)技术在控制领域的最新进展进行了综述,内容主要包括三类基本方法,即:基于解析模型的FDD、基于信号处理和基于知识的故障检测与诊断方法。重点评述了近年来发展起来的信息融合方法、多Agent方法、鲁棒故障检测、网络控制系统的故障诊断等。最后介绍了故障检测与诊断技术在控制系统中的若干应用成果,并指出尚待解决的主要问题和值得进一步研究的方向。     

Robust fault detection filter and its application in MEMS-based INS/GPS

Since any disturbance and fault may lead to significant performance degradation in practical dynamical systems,it is essential for a system to be robust to disturbances but sensitive to faults.For this purpose,this paper proposes a robust fault-detection filter for linear discrete time-varying systems.The algorithm uses H∞ estimator to minimize the worst possible amplification from disturbances to estimate errors,and H_ index to maximize the minimum effect of faults on the residual output of the filter.This approach is applied to the MEMS-based INS/GPS.And simulation results show that the new algorithm can reduce the effect of unknown disturbances and has a high sensitivity to faults.     

Robust fault detection and diagnosis for uncertain nonlinear systems

This paper considers robust fault detection and diagnosis for input uncertain nonlinear systems. It proposes a multi-objective fault detection criterion so that the fault residual is sensitive to the fault but insensitive to the uncertainty as much as possible. Then the paper solves the proposed criterion by maximizing the smallest singular value of the transformation from faults to fault detection residuals while minimizing the largest singular value of the transformation from input uncertainty to the fault detection residuals. This method is applied to an aircraft which has a fault in the left elevator or rudder. The simulation results show the proposed method can detect the control surface failures rapidly and efficiently.