Actuator Fault Estimation Scheme for Flight Applications

2002 ◽  
Vol 124 (4) ◽  
pp. 701-704 ◽  
Author(s):  
Jiong-Sang Yee ◽  
Jian Liang Wang ◽  
Bin Jiang
Keyword(s):  
Flight Control ◽  
Fault Tolerant ◽  
Fault Estimation ◽  
Actuator Fault ◽  
Flight Control System ◽  
Fighter Aircraft ◽  
Flying Qualities ◽  
Estimation Scheme ◽  
On Line ◽  
Loss Of Actuator Effectiveness

The paper presents a new actuator fault estimation scheme based on the augmented error method that estimates the actuator effectiveness on-line. The proposed scheme is applied to a fault-tolerant flight control system design for an F4-E fighter aircraft. The output of a nominal H∞ controller is continuously reconfigured to compensate for any loss of actuator effectiveness. Simulation results demonstrate good fault estimation and flying qualities obtained using the proposed scheme under the actuator fault conditions.

Parameter-dependent actuator fault estimation for vehicle active suspension systems based on RBFNN

2021 ◽  
pp. 095440702199301
Author(s):  
Wenping Xue ◽  
Pan Jin ◽  
Kangji Li
Keyword(s):  
Fault Tolerant ◽  
External Disturbance ◽  
Active Suspension ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Actuator Fault ◽  
Mass Variation ◽  
Fe Method ◽  
Comparison Results ◽  
Parameter Dependent

The actuator fault estimation (FE) problem is addressed in this study for the quarter-car active suspension system (ASS) with consideration of the sprung mass variation. Firstly, the ASS is modeled as a parameter-dependent system with actuator fault and external disturbance input. Then, a parameter-dependent FE observer is designed by using the radial basis function neural network (RBFNN) to approximate the actuator fault. In addition, the design conditions are turned into a linear matrix inequality (LMI) problem which can be easily solved with the aid of LMI toolbox. Finally, simulation and comparison results are given to show the accuracy and rapidity of the proposed FE method, as well as good adaptability against the sprung mass variation. Moreover, a simple FE-based active fault-tolerant control (AFTC) strategy is provided to further demonstrate the effectiveness and applicability of the proposed FE method.

scholarly journals Fixed-Time Sliding-Mode Fault-Tolerant Control of Waste Heat Power Generator Systems

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Zhi Wang ◽  
Yateng Bai ◽  
Jin Xie ◽  
Zhijie Li ◽  
Caoyuan Ma ◽  
...  
Keyword(s):  
Fault Tolerant ◽  
Waste Heat ◽  
Sliding Mode ◽  
Dynamic Performance ◽  
Tracking Error ◽  
Fixed Time ◽  
Fault Estimation ◽  
Actuator Fault ◽  
Heat Power ◽  
Time Control

In order to overcome disturbances such as the instability of internal parameters or the actuator fault, the time-varying proportional-integral sliding-mode surface is defined for coordinated control of the excitation generator and the steam valve of waste heat power generation units, and a controller based on sliding-mode function is designed which makes the system stable for a limited time and gives it good performance. Based on this, a corresponding fault estimation law is designed for specific faults of systems, and a sliding-mode fault-tolerant controller is constructed based on the fixed-time control theory so that the systems can still operate stably when an actuator fault occurs and have acceptable performance. The simulation results show that the tracking error asymptotically tends to be zero, and the fixed-time sliding-mode fault-tolerant controller can obviously improve the dynamic performance of the system.

scholarly journals Design and Analysis for Early Warning of Rotor UAV Based on Data-Driven DBN

Electronics ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1350 ◽  
Author(s):  
Chen ◽  
Wu ◽  
Wu ◽  
Xiong ◽  
Han ◽  
...  
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fault Diagnosis ◽  
Early Warning ◽  
Flight Control ◽  
Data Driven ◽  
Diagnostic Model ◽  
Flight Control System ◽  
Model Based ◽  
On Line

The unmanned aerial vehicle (UAV), which is a typical multi-sensor closed-loop flight control system, has the properties of multivariable, time-varying, strong coupling, and nonlinearity. Therefore, it is very difficult to obtain an accurate mathematical diagnostic model based on the traditional model-based method; this paper proposes a UAV sensor diagnostic method based on data-driven methods, which greatly improves the reliability of the rotor UAV nonlinear flight control system and achieves early warning. In order to realize the rapid on-line fault detection of the rotor UAV flight system and solve the problems of over-fitting, limited generalization, and long training time in the traditional shallow neural network for sensor fault diagnosis, a comprehensive fault diagnosis method based on deep belief network (DBN) is proposed. Using the DBN to replace the shallow neural network, a large amount of off-line historical sample data obtained from the rotor UAV are trained to obtain the optimal DBN network parameters and complete the on-line intelligent diagnosis to achieve the goal of early warning as possible as quickly. In the end, the two common faults of the UAV sensor, namely the stuck fault and the constant deviation fault, are simulated and compared with the back propagation (BP) neural network model represented by the shallow neural network to verify the effectiveness of the proposed method in the paper.

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