An MMAE failure detection system for the F-16

A multiple model adaptive estimation (MMAE) algorithm is implemented with the fully nonlinear six-degree-of-motion, Simulation Rapid-Prototyping facility (SRF) VISTA F-16 software simulation tool. The algorithm is composed of a bank of Kalman filters modeled to match particular hypotheses of the real world. Each presumes a single failure in one of the flight-critical actuators, or sensors, and one presumes no failure. For dual failures, a hierarchical structure is used to keep the number of on-line filters to a minimum. The algorithm is demonstrated to be capable of identifying flight-critical aircraft actuator and sensor failures at a low dynamic pressure (20,000 ft, 0.4 Mach). Research includes single and dual complete failures. Tuning methods for accommodating model mismatch, including addition of discrete dynamics pseudonoise and measurement pseudonoise, are discussed and demonstrated. Scalar residuals within each filter are also examined and characterized for possible use as an additional failure declaration voter. An investigation of algorithm performance off the nominal design conditions is accomplished as a first step towards full flight envelope coverage     

Performance enhancement of a multiple model adaptive estimator

We describe performance improvement techniques for a multiple model adaptive estimator (MMAE) used to detect and identify control surface and sensor failures on an unmanned flight vehicle. Initially failure identification was accomplished within 4 s of onset, but by removing the “β dominance” effects, bounding the hypothesis conditional probabilities, retuning the Kalman filters, increasing the penalty for measurement residuals, decreasing the probability smoothing, and increasing residual propagation, the identification time was reduced to 2 s     

Multiple-model adaptive estimation using a residual correlationKalman filter bank

We propose a modified multiple model adaptive estimation (MMAE) algorithm that uses the time correlation of the Kalman filter residuals, in place of their scaled magnitude, to assign conditional probabilities for each of the modeled hypotheses. This modified algorithm, denoted the residual correlation Kalman filter bank (RCKFB), uses the magnitude of an estimate of the correlation of the residual with a slightly modified version of the usual MMAE hypothesis testing algorithm to assign the conditional probabilities to the various hypotheses that are modeled in the Kalman filter bank within the MMAE. This concept is used to detect flight control actuator failures, where the existence of a single frequency sinusoid (which is highly time correlated) in the residual of an elemental filter within an MMAE is indicative of that filter having the wrong actuator failure status hypothesis. This technique results in a delay in detecting the flight control actuator failure because several samples of the residual must be collected before the residual correlation can be estimated. However, it allows a significant reduction of the amplitude of the required system inputs for exciting the various system modes to enhance identifiability, to the point where they may possibly be subliminal, so as not to be objectionable to the pilot and passengers     

MMAE-based control redistribution applied to the VISTA F-16

A novel control technique, termed control redistribution, is presented and applied in conjunction with multiple model adaptive estimation (MMAE) to the variable in-night stability test aircraft (VISTA) F-16, to detect and compensate for sensor and/or actuator failures. This ad hoc method redistributes control commands (that would normally be sent to failed actuators) to the nonfailed actuators, accomplishing the same control action on the aircraft. Dither is considered to help disambiguate failures in the longitudinal and lateral-directional channels. Detection of both single-actuator and single-sensor failures is considered. Failures are demonstrated detectable in less than 1 s, with an aircraft output nearly identical to that anticipated from a fully functional aircraft in the same environment     

Multiple model adaptive estimation with filter spawning

Multiple model adaptive estimation (MMAE) with filter spawning is used to detect and estimate partial actuator failures on the VISTA F-16. The truth model is a full six-degree-of-freedom simulation provided by Calspan and General Dynamics. The design models are chosen as 13-state linearized models, including first order actuator models. Actuator failures are incorporated into the truth model and design model assuming a "failure to free stream." Filter spawning is used to include additional filters with partial actuator failure hypotheses into the MMAE bank. The spawned filters are based on varying degrees of partial failures (in terms of effectiveness) associated with the complete-actuaton-failure hypothesis with the highest conditional probability of correctness at the current time. Thus, a blended estimate of the failure effectiveness is found using the filters' estimates based upon a no-failure hypothesis, a complete actuator failure hypothesis, and the spawned filters' partial-failure hypotheses. This yields substantial precision in effectiveness estimation, compared with what is possible without spawning additional filters, making partial failure adaptation a viable methodology.     

基于多模型的飞控系统自适应重构技术研究

针对飞控系统执行器故障引起参数大范围跳变的问题,提出了一种基于多模型的自适应重构控制方法。建立了执行器故障参数模型,根据故障的特征模型设计一系列并行的辨识模型,采用固定模型与自适应模型相结合的方式,依据转换标准选择与当前飞机状态最匹配的辨识模型所对应的控制器。通过对某型飞机侧向控制系统进行仿真,表明在执行器严重受损的情况下,飞机仍能保持良好的性能。     

Closed-loop dynamic control allocation for aircraft with multiple actuators

A closed-loop control allocation method is proposed for a class of aircraft with multiple actuators. Nonlinear dynamic inversion is used to design the baseline attitude controller and derive the desired moment increment. And a feedback loop for the moment increment produced by the deflections of actuators is added to the angular rate loop, then the error between the desired and actual moment increment is the input of the dynamic control allocation. Subsequently, the stability of the closed-loop dynamic control allocation system is analyzed in detail. Especially, the closedloop system stability is also analyzed in the presence of two types of actuator failures: loss of effectiveness and lock-in-place actuator failures, where a fault detection subsystem to identify the actuator failures is absent. Finally, the proposed method is applied to a canard rotor/wing (CRW) aircraft model in fixed-wing mode, which has multiple actuators for flight control. The nonlinear simulation demonstrates that this method can guarantee the stability and tracking performance whether the actuators are healthy or fail.     

Enhanced motion and sizing of bank in moving-bank MMAE

The focus of this research is to provide methods for generating precise parameter estimates in the face of potentially significant parameter variations such as system component failures. The standard multiple model adaptive estimation (MMAE) algorithm uses a bank of Kalman filters, each based on a different model of the system. Parameter discretization within the MMAE refers to selection of the parameter values assumed by the elemental Kalman filters, and dynamically redeclaring such discretization yields a moving-bank MMAE. A new online parameter discretization method is developed based on the probabilities associated with the generalized chi-squared random variables formed by residual information from the elemental Kalman filters within the MMAE. This new algorithm is validated through computer simulation of an aircraft navigation system subjected to interference/jamming while attempting a successful precision landing of the aircraft.     

小型化高负载飞行器前轮转弯控制系统研究

介绍了一种前轮转弯控制系统,主要由转弯机构、控制器和位移传感器组成。转弯机构采用丝杠拨叉式传动方案,实现小型化、高负载的要求;控制器采用双冗余422总线通信设计方案,保证通信链路可靠性;通过采集线位移、角位移传感器两路反馈信号,实现位置闭环运算和前轮摆角实时监测。经地面及飞行试验验证,本系统各项指标均能满足要求。     

Design of passive fault-tolerant flight controller against actuator failures

The problem of designing passive fault-tolerant flight controller is addressed when the normal and faulty cases are prescribed. First of all, the considered fault and fault-free cases are formed by polytopes. As considering that the safety of a post-fault system is directly related to the maximum values of physical variables in the system, peak-to-peak gain is selected to represent the relationships among the amplitudes of actuator outputs, system outputs, and reference commands. Based on the parameter dependent Lyapunov and slack methods, the passive fault-tolerant flight controllers in the absence/presence of system uncertainty for actuator failure cases are designed, respectively. Case studies of an airplane under actuator failures are carried out to validate the effectiveness of the proposed approach     

基于神经网络的超机动飞机自适应重构控制

 讨论了一种基于神经网络的超机动飞机直接自适应重构控制方法。飞机的基本控制律采用非线性动态逆方法设计,对于模型不准确和舵面故障等因素导致的逆误差采用神经网络进行在线补偿。通过仿真表明,在飞机发生舵面故障时,神经网络通过自适应地补偿逆误差,可以快速在线重构控制律,保持飞机稳定和一定的操纵品质。     

Reconfigurable flight control via multiple model adaptive controlmethods

An aircraft flight control system with reconfigurable capabilities is considered. A multiple model adaptive controller (MMAC) is shown to provide effective reconfigurability when subjected to single and double failures of sensors and/or actuators. A command generator tracker/proportional-plus-integral/Kalman filter (CGT/PI/KF) form of controller was chosen for each of the elemental controllers within the MMAC algorithm and each was designed via LQG synthesis to provide desirable vehicle behavior for a particular failure status of sensors and actuators. The MMAC performance is enhanced by an alternate computation of the MMAC hypothesis probabilities, use of maximum a posteriori probability (MAP) versus Bayesian form of the MAC (or a modified combination of both), and reduction of identification ambiguities through scalar residual monitoring for the case of sensor failures     

Detection of interference/jamming and spoofing in a DGPS-aidedinertial system

Previous research at the Air Force Institute of Technology (AFIT) has resulted in the design of a differential Global Positioning System (DGPS) aided INS-based (inertial navigation system) precision landing system (PLS) capable of meeting the FAA precision requirements for instrument landings. The susceptibility of DGPS transmissions to both intentional and nonintentional interference/jamming and spoofing must be addressed before DGPS may be safely used as a major component of such a critical navigational device. This research applies multiple model adaptive estimation (MMAE) techniques to the problem of detecting and identifying interference/jamming and spoofing in the DGPS signal. Such an MMAE is composed of a bank of parallel filters, each hypothesizing a different failure status, along with an evaluation of the current probability of each hypothesis being correct, to form a probability-weighted average state estimate as an output. For interference/jamming degradation represented as increased measurement noise variance, simulation results show that, because of the good failure detection and isolation (FDI) performance using MMAE, the blended navigation performance is essentially that of a single extended Kalman filter (EKF) artificially informed of the actual interference noise variance. However, a standard MMAE is completely unable to detect spoofing failures (modeled as a bias or ramp offset signal directly added to the measurement). This work describes a moving-bank pseudoresidual MMAE (PRMMAE) to detect and identify such spoofing. Using the PRMMAE algorithm, spoofing is very effectively detected and isolated; the resulting navigation performance is equivalent to that of an EKF operating in an environment without spoofing     

Characterization of Kalman filter residuals in the presence ofmismodeling

The mean and covariance of a Kalman filter residual are computed for specific cases in which the Kalman filter model differs from a linear model that accurately represents the true system (the truth model). Multiple model adaptive estimation (MMAE) uses a bank of Kalman filters, each with a different internal model, and a hypothesis testing algorithm that uses the residuals from this bank of Kalman filters to estimate the true system model. At most, only one Kalman filter model will exactly match the truth model and will produce a residual whose mean and standard deviation have already been analyzed. All of the other filters use internal models that mismodel the true system. We compute the effects of a mismodeled input matrix, output matrix, and state transition matrix on these residuals. The computed mean and covariance are compared with simulation results of flight control failures that correspond to mismodeled input matrices and output matrices     

MIMO变结构飞行重构控制系统设计

基于滑模变结构控制,提出一种MIMO(multiple input multiple output)的飞行重构控制系统的频域设计方法.将滑模变结构控制与飞行重构控制相结合,解决了飞行重构控制技术中故障检测和系统参数辨识的问题.引入渐近观测器和hedge模型增加重构控制系统对衍生未建模动态的鲁棒性;引入作动器模型、输出饱和限制和驾驶员模型,使变结构重构控制系统设计方法变得更为有效和实用;以某型飞机的横航向飞行控制系统为例,进行设计模拟.结果表明:在飞机气动参数大幅突变和操纵面严重受损的情况下,飞机仍能保持良好的性能.      

On-line diagnostics of a self-contained flight actuator

A mathematical model describing the dynamics of a self-contained flight control actuator is established. Typical failures of the actuator are defined in the space of the model parameters in the form of a failure pattern library. A diagnostic model of the actuator, intentionally sensitive to particular failures, is defined. A diagnostic procedure, featuring on-line parameter estimation of the diagnostic model, failure detection, and isolation, is proposed. A failure prediction procedure, utilizing trends exhibited by parameter estimates, is formulated. The results are verified by computer simulation     

Reconfigurable fault-tolerant control for supersonic missiles with actuator failures under actuation redundancy

Aircraft undergoing actuator failures into under-actuation have been seldom studied in literature. Aiming at addressing actuator failures of Total Loss of Effectiveness (TLOE) as well as Partial Loss of Effectiveness (PLOE) resulting in different system actuations, reconfigurable Fault-Tolerant Control (FTC) is proposed for supersonic wingless missiles under actuation redundancy. The under-actuated system of TLOE failure patterns is solved by transformation to cascade systems through a ‘shape variable’. Meanwhile, actuator TLOE faults of different unknown failure patterns from proper actuation to under-actuation are accommodated by a reconfigurable adaptive law on a multiple-model basis. The backstepping technique with the Extended State Observer (ESO) method adopted as a basic strategy is applied to an established symmetric coupled missile system with actuator PLOE faults, modeling errors, and external disturbances. Additionally, the nonlinear saturation characteristics of actuators are settled by an auxiliary system with the Nussbaum function technique. The stability of the control system is analyzed and proven through Lyapunov theory. Numerical simulations are implemented in the presences of aerodynamic uncertainties, gust disturbance, and actuator failures. Results demonstrate the effectiveness of the proposed method with satisfactory tracking performance and actuator fault tolerance capacity.     

基于光纤传感的襟翼操纵载荷试飞技术

为了研究民用飞机减速板打开引起的襟翼载荷增量,验证襟翼中小偏度下的严重操纵载荷准确性,避免成本高昂的特殊构型试验件研制和减少机上管线敷设空间限制等问题,针对某具体型号襟翼运动机构,建立了基于光纤传感的操纵载荷测量系统、测量系统校准方法,完成襟翼作动器操纵载荷和翼面总载荷的直接验证与确认。试飞实施结果表明,基于光纤传感的襟翼操纵载荷识别及测试技术在某型号减速板打开后襟翼操纵载荷试飞中的研究应用,为襟翼操纵载荷验证提供了一种有效的高精度、低成本试飞测试方法。     

基于NFTET的高超声速飞行器再入容错制导

针对以X-33为对象的三自由度高超声速飞行器,采用相邻可行轨迹存在定理(NFTET)设计了容错制导律以解决再入段执行器发生故障的轨迹重构问题。在标称情况下采用预测校正算法生成满足再入过程约束和终端约束要求的再入轨迹;当执行器发生故障时,飞行器气动参数、结构和舵面力矩都可能发生不可预测的变化,原先的轨迹不再满足制导要求,因此需要设计新型容错制导律。针对实际再入制导模型,基于NFTET设计容错制导算法对轨迹进行重构,得到满足故障情况下制导任务的可行轨迹。从仿真结果中可以看出,容错制导算法生成的新轨迹重新回到了约束范围之内,轨迹呈收敛趋势,使得高超声速飞行器从故障恢复到正常飞行状态,提高了飞行器的自主容错能力。     

THE DECENTRALIZED ROBUST FAULT TOLERANT CONTROL FOR THE SENSOR FAILURE OF THE FIGHTER

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