Integrated fault estimation and fault-tolerant control for a flexible regional aircraft

The article focuses on the design and application of an active reconfigurable controller that mitigates the effects of gust load and actuator faults on a flexible aircraft. A novel integrated adaptive output feedback scheme is investigated to address the actuator faults. The real-time fault values provided by the fault estimation module are considered in the reconfigurable control law to improve the fault-tolerant capability. The estimate values of faults and control gains are calculated by anal...     

航天器自适应快速非奇异终端滑模容错控制

针对存在外部干扰、转动惯量矩阵不确定、控制器饱和以及执行器故障的航天器姿态跟踪控制问题,提出了基于自适应快速非奇异终端滑模的有限时间收敛控制方案。通过引入能够避免奇异点的具有有限时间收敛特性的快速非奇异终端滑模面,设计了满足多约束的有限时间姿态跟踪容错控制器,并利用参数自适应方法使控制器设计不依赖于系统惯量信息和外部干扰的上界。此外,所设计的控制器显式考虑了执行器输出力矩的饱和幅值特性,使航天器在饱和幅值的限制下完成姿态跟踪控制任务,并且无须进行在线故障估计。Lyapunov稳定性分析表明：在外部干扰、转动惯量矩阵不确定、控制器饱和以及执行器故障等约束条件下,所设计的控制器能够保证闭环系统的快速收敛性,而且对控制器饱和与执行器故障具有良好的容错性能。数值仿真校验了该控制器在姿态跟踪控制中的优良性能。     

尾座式无人飞行器鲁棒容错编队控制

针对尾座式无人飞行器编队在执行器故障、严重的非线性和耦合性、参数不确定性、外界扰动等影响下的容错控制问题进行了研究。提出了一种鲁棒容错编队控制方法来实现一群尾座式无人飞行器在执行器故障情况下的期望编队飞行。所构建的控制器由2部分组成：标称控制器和干扰补偿控制器。设计标称控制器使系统实现期望的控制性能,利用干扰补偿控制器抑制多种不确定性和执行器故障的影响。通过理论分析证明了系统的鲁棒稳定性,并通过数值仿真验证了算法的有效性。     

Efficient fault tolerant estimation using the IMM methodology

Space systems are characterized by a low-intensity process noise resulting from uncertain forces and moments. In many cases, their scalar measurement channels can be assumed to be independent, with one-dimensional internal dynamics. The nominal operation of these systems can be severely damaged by faults in the sensors. A natural method that can be used to yield fault tolerant estimates of such systems is the interacting multiple model (IMM) filtering algorithm, which is known to provide very accurate results. However, having been derived for a general class of systems with switching parameters, the IMM filter does not utilize the independence of the measurement errors in different channels, nor does it exploit the fact that the process noise is of low intensity. Thus, the implementation of the IMM in this case is computationally expensive. A new estimation technique is proposed herein, that explicitly utilizes the aforementioned properties. In the resulting estimation scheme separate measurement channels are handled separately, thus reducing the computational complexity. It is shown that, whereas the IMM complexity is exponential in the number of fault-prone measurements, the complexity of the proposed technique is polynomial. A simulation study involving spacecraft attitude estimation is carried out. This study shows that the proposed technique closely approximates the full-blown IMM algorithm, while requiring only a modest fraction of the computational cost.     

基于模态切换的航空发动机容错控制

综合了航空发动机控制和故障诊断方法,设计了基于模态切换的任务级和发动机级模式的容错控制系统.任务级模式在发动机部件故障时,通过切换控制策略和控制模式达到恢复或降低发动机性能的要求;发动机级模式在控制回路失效时,根据故障情况切换到容错控制回路,从而保证发动机继续正常工作.数字仿真结果表明:在稳态或加速过程中出现部件故障时,容错控制系统都能够100%恢复发动机的推力;在发动机中间、慢车和节流状态下,当压气机转速控制回路失效时,容错控制系统能够在3s内平稳切换到风扇转速控制回路.      

Maneuvering target tracking using IMM method at high measurementfrequency

The problem of tracking a maneuvering target with a high measurement frequency is considered. The measurement noise is significantly correlated when the measurement frequency is high. A simple decorrelation process is proposed to enhance the interacting multiple model (IMM) algorithm to track a maneuvering target with correlated measurement noise. It is found that the decorrelation process may improve system performance significantly, especially in velocity and acceleration estimations     

航天器有限时间自适应姿态跟踪容错控制

非刚体航天器存在时变的惯量、执行器完全失效或衰退故障以及外界干扰的情况,提出一种有限时间自适应姿态跟踪容错控制方法。首先,基于有限时间理论和自适应方法,设计惯量不确定性自适应估计项和外界干扰参数自适应估计项进行系统补偿,克服惯量不确定性和抑制外界干扰;然后,基于容错控制和双幂次方法,设计一种自适应有限时间姿态跟踪容错控制算法,并且利用Lyapunov稳定性理论证明所提算法能够保证航天器姿态跟踪系统实际有限时间稳定;最后,对仿真结果进行验证。结果表明:所提有限时间姿态跟踪容错控制方法是有效的。     

基于反步法的航天器有限时间姿态跟踪容错控制

针对存在外部干扰、控制饱和以及执行器故障的航天器姿态跟踪控制问题,提出了基于反步法的有限时间控制方案。通过引入一类新型的具有有限时间收敛特性的积分式滑模面,设计了满足多约束的有限时间容错姿态跟踪控制器,并利用参数自适应方法使控制器设计不依赖于系统惯量信息和外部干扰的界。该容错控制方案的设计无需在线故障信息检测、分离甚至控制器重构,并显式地考虑了执行器输出的饱和幅值要求。稳定性分析表明:在控制饱和甚至执行器故障等多约束的条件下,本文所设计的控制器不仅保证了姿态跟踪的有限时间收敛性,且对于执行器故障具有优越的容错能力;数值仿真分析进一步验证了该控制器的控制性能,以及对外部干扰和系统不确定性的鲁棒性。     

基于自适应动态规划的运载火箭智能姿态容错控制

针对运作火箭主动段发动机摆动执行机构故障下的姿态控制问题,结合自适应动态规划（ADP）方法设计了一种智能容错控制策略。该智能容错控制器主要包括2部分：容错稳定控制部分和优化补偿部分。容错稳定控制部分利用自适应和滑模变结构控制设计,主要维持执行机构故障下姿态控制系统的稳定,保证姿态跟踪误差的有限时间收敛;优化补偿部分采用执行-评价结构,利用ADP的在线学习优势,根据姿态系统的跟踪误差（尤其是系统故障、强干扰导致的跟踪偏差）,设计ADP算法产生补偿控制来进一步优化姿态控制系统的跟踪性能。仿真验证表明,即使存在外部干扰和执行机构故障的情况下,所提方法仍能保证系统稳定且精确跟踪指令信号。     

涡轴发动机数控系统控制规律及容错控制

用Simulink仿真工具,建立了某涡轴发动机及执行机构的数学模型,对涡轴发动机数控系统的稳态控制规律、加减速控制规律,关键传感器故障后的容错控制规律进行了仿真研究,提出了涡轴发动机控制的完整解决方案.仿真结果表明,该控制方案能在无故障和有故障的情况下,保证控制系统稳定工作,并具有较好的稳态和动态性能.     

高超声速飞行器自适应神经网络容错控制

针对高超声速飞行器巡航段执行器控制效益损失故障和卡死故障问题,基于高超声速飞行器纵向运动模型,将自适应算法与改进的径向基函数神经网络(RBFNN)方法相结合,设计了一种自适应神经网络容错控制器。所提出的容错控制方法具有无需估计执行器故障值的优点,且设计的控制算法结构简单,无需大量实时计算,可以快速处理故障的发生,确保系统在参数不确定、恒定或时变执行器故障与卡死故障情况下仍具有稳定跟踪能力。最后,仿真验证了该方法的有效性。     

Precision large scale air traffic surveillance using IMM/assignmentestimators

We present the development and implementation of a multisensor-multitarget tracking algorithm for large scale air traffic surveillance based on interacting multiple model (IMM) state estimation combined with a 2-dimensional assignment for data association. The algorithm can be used to track a large number of targets from measurements obtained with a large number of radars. The use of the algorithm is illustrated on measurements obtained from 5 FAA radars, which are asynchronous, heterogeneous, and geographically distributed over a large area. Both secondary radar data (beacon returns from cooperative targets) as well as primary radar data (skin returns from noncooperative targets) are used. The target IDs from the beacon returns are not used in the data association. The surveillance region includes about 800 targets that exhibit different types of motion. The performance of an IMM estimator with linear motion models is compared with that of the Kalman filter (KF). A number of performance measures that can be used on real data without knowledge of the ground truth are presented for this purpose. It is shown that the IMM estimator performs better than the KF. The advantage of fusing multisensor data is quantified. It is also shown that the computational requirements in the multisensor case are lower than in single sensor case, Finally, an IMM estimator with a nonlinear motion model (coordinated turn) is shown to further improve the performance during the maneuvering periods over the IMM with linear models     

零质量射流与分离控制的数值模拟

在非定常可压缩方程的求解当中引入预处理方法、多重网格等加速收敛技术,提高了可压缩方法处理低速问题的效率和精度。利用该方法对两个流动控制算例进行了数值模拟,首先模拟了零质量射流的外部流场,从射流中心线上的速度分布、射流宽度等方面均得到了和实验较为一致的结果。之后模拟了不同控制下的绕二维翼型的分离流动,包括有定常吸气和零质量射流,两种方法都不同程度上使分离泡长度缩小,分离区的压力升高,一定程度上显示了两种方法在分离流动控制上的应用潜力。     

考虑预设性能约束的运输机姿态容错控制

针对运输机舵面故障情况下的姿态容错控制问题,提出了一种考虑预设性能约束的自适应指令滤波增量反步(Adaptive Command-filtered Incremental Backstepping,ACFIBS)容错控制器。首先,构造运输机故障模型,在反步控制设计结构下,通过构造预设性能函数,保证外回路姿态角跟踪误差的动态性能。然后,考虑舵机偏转速率和幅值限制,引入受限指令滤波器和补偿信号,综合考虑气动参数不确定性,采用增量方法设计反步内环控制律。在此基础上,进一步考虑舵面故障情况,引入自适应方法及低通滤波器改进增量反步控制器。最后,通过理论推导和仿真试验验证了控制方法的有效性。仿真结果表明,所设计的控制器具有良好的容错性能,在不同舵面故障条件下均可实现对指令信号的预设性能跟踪,且在参数摄动情况下具有较强的鲁棒性。     

Robust fault-tolerant control for wing flutter under actuator failure

Many control laws, such as optimal controller and classical controller, have seen their applications to suppressing the aeroelastic vibrations of the aeroelastic system. However, those control laws may not work effectively if the aeroelastic system involves actuator faults. In the current study for wing flutter of reentry vehicle, the effect of actuator faults on wing flutter system is rarely considered and few of the fault-tolerant control problems are taken into account. In this paper, we use the radial basis function neural network and the finite-time H_∞ adaptive fault-tolerant control technique to deal with the flutter problem of wings, which is affected by actuator faults, actuator saturation, parameter uncertainties and external disturbances. The theory of this article includes the modeling of wing flutter and fault-tolerant controller design. The stability of the finite-time adaptive fault-tolerant controller is theoretically proved. Simulation results indicate that the designed fault-tolerant flutter controller can effectively deal with the faults in the flutter system and can promptly suppress the wing flutter as well.     

Tracking of multiple maneuvering targets using multiscan JPDA and IMM filtering

The paper considers the problem of tracking multiple maneuvering targets in the presence of clutter using switching multiple target motion models. A novel suboptimal filtering algorithm is developed by applying the basic interacting multiple model (IMM) approach and the joint probabilistic data association (JPDA) technique. Unlike the standard single-scan JPDA approach, the authors exploit a multiscan joint probabilistic data association (mscan-JPDA) approach to solve the data association problem. The algorithm is illustrated via a simulation example involving tracking of four maneuvering targets and a multiscan data window of length two     

Fault Detection and Diagnosis of Aircraft Actuators using Fuzzy-Tuning IMM Filter

This paper proposes a new interacting multiple model (IMM) filter for actuator fault detection. Since each individual filter of the IMM filter uses the combined information of the estimation values from all the operating filters, it can effectively estimate system parameter variations, thereby it can diagnose the actuator damage with an unknown magnitude. In this study, to diagnose the actuator failure fast and accurately, fuzzy logic is used to tune a transition probability among multiple models. This makes the fault detection process smooth and reduces the possibility of false fault detection. Also, a discrete fault tolerant command tracker is derived to cope with actuator damages. To validate the performance of the proposed fault detection and diagnosis (FDD) algorithm, numerical simulations are performed for a high performance aircraft system.     

双目标约束下的航空发动机分布式控制系统最优保成本容错控制

针对带参数摄动、Markov时延、数据丢包和外部干扰的航空发动机分布式控制系统,研究了当执行机构发生部分失效故障时的被动容错控制问题,在H∞性能指标和成本性能指标双重约束下设计了最优保成本容错控制器.首先对系统模型中的各不确定参数进行量化描述,并在此基础上建立整个闭环系统的增广模型;其次证明了双目标约束下闭环系统渐进稳定的充分条件,并给出保成本容错控制器的设计方法;基于双目标相容性理论,得到最优保成本容错控制律的求解方法.仿真结果表明最优保成本容错控制器能够在执行机构发生区间内的任一随机故障时保证闭环系统渐进稳定,并具备一定的H∞性能.且当发动机低压转子转速发生1%阶跃变化时,最优保成本容错控制器的主燃油流量和尾喷管临界截面积峰值仅为最优鲁棒H∞容错控制器的16.03%和16.93%.     

基于干扰观测器的四旋翼无人机离散时间容错控制

为了飞行控制方案便于在计算机上实现,针对具有外部干扰和执行器加性故障的四旋翼无人机（UAV）角度运动方程,给出一种基于干扰观测器的离散时间跟踪控制方案。通过设计离散时间干扰观测器抑制外部干扰和执行器故障的不利影响,并结合干扰观测器设计离散时间控制器。通过数值仿真验证了基于干扰观测器的离散时间容错控制方案的有效性。仿真结果表明,设计的离散控制器能够保证外部干扰和执行器故障综合作用下的四旋翼UAV系统跟踪控制性能。     

A high-safety active/passive hybrid control approach for compressor surge based on nonlinear model predictive control

Surge active control can expand the stable operating range of the compressor. However, the difficulty of flow measurement, dynamic uncertainty disturbance, actuator delay characteristics, hard constraints of control variable, and system security measures have not been fully considered in the existing active control system, which significantly hinders its engineering application. Therefore, a nonlinear model predictive surge active control method is first presented based on flow estimator designed by using a continuous-time Kalman filter for dealing with the hard constraint of control variable and the impact of actuator delay of compression system with dynamic uncertainty. Then, a high-safety active/surge passive hybrid control strategy is designed, dominated by the surge active control and supplemented by the surge passive control, to ensure the compression system’s safe and stable operation. Lastly, the simulation results suggest that the flow estimator accurately estimates the compressor flow. When considering the delay impact of the actuators and sensors and measurement noise on the system, the proposed method exhibits stronger robustness than the existing methods. The active/surge passive hybrid control strategy can successfully ensure the compression system's safe and stable operation. This paper is of high practical significance for the engineering application of future compressor surge active control technologies.