Adaptive observer-based fault diagnosis for sensor in a class of MIMO nonlinear system

Author(s):  
Qi Ding ◽  
Xiafii Peng ◽  
Xiaoli Zhang ◽  
Xiaoqiang Hu ◽  
Xunyu Zhong
Author(s):  
Qizhi He ◽  
Weiguo Zhang ◽  
Degang Huang ◽  
Huakun Chen ◽  
Jinglong Liu

Optimal two stage Kalman filter (OTSKF) is able to obtain optimal estimation of system states and bias for linear system which contains random bias. Unscented Kalman filter (UKF) is a conventional nonlinear filtering method which utilizes Sigmas point sampling and unscented transformation technology realizes propagation of state means and covariances through nonlinear system. Aircraft is a typical complicate nonlinear system, this paper treats the faults of Inertial Measurement Unit (IMU) as random bias, established a filtering model which contains faults of IMU. Hybird the two stage filtering technique and UKF, this paper proposed an optimal two stage unscented Kalman filter (OTSUKF) algorithm which is suitable for fault diagnosis of IMU, realized optimal estimation of system states and faults identification of IMU via proposed innovative designing method of filtering model and the algorithm was validated that it is robust to wind disterbance via real flight data and it is also validated that proposed OTSUKF is optimal in the existance of wind disturbance via comparing with the existance iterated optimal two stage extended kalman filter (IOTSEKF) method.


Author(s):  
Jinhua Fan ◽  
Youmin Zhang ◽  
Zhiqiang Zheng

A challenging problem on observer-based, integrated fault diagnosis and fault-tolerant control for linear systems subject to actuator faults and control input constraints is studied in this paper. An adaptive observer approach is used for the joint state-fault magnitude estimation, and a feedback controller is designed to stabilize the closed-loop system without violating the actuator limits in the presence of actuator faults. Matrix inequality conditions are provided for computation of design parameters of the observer and the feedback controller, and the admissible initial conditions and estimation errors are bounded by invariant ellipsoidal sets. The design results are closely related to the fault magnitude and variation rate, and a necessary condition on the admissible fault magnitudes dependent on the control limits is directly obtained from the design process. The proposed design framework allows a direct application of the pole placement method to obtain stabilization results. To improve the system performance, a nonlinear programming-based optimization algorithm is proposed to compute an optimized feedback gain, whereas the one obtained by pole placement can be taken as an initial feasible solution for nonlinear optimization. Numerical studies with two flight control systems demonstrate the effectiveness of proposed design techniques.


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