Parameter Estimation-Based Fault Detection, Isolation and Recovery for Nonlinear Satellite Models

Jiang, Tao; Khorasani, K.; Tafazoli, Siamak

doi:10.1109/tcst.2007.906317

Cited by 110 publications

(70 citation statements)

References 15 publications

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“…si ðR i þ s 2 1 S i ÞA si : In view of Schur complement, (7) implies that X i < 0. Then we have _ V i ðt; n t Þ þ aV i ðt; n t Þ < 0 for all g 1 (t) -0.…”

Section: Resultsmentioning

confidence: 99%

“…Many interesting approaches have been presented and applied to practical processes, such as the observer-based method [1][2][3], the parity space approach [4][5][6], and the parameter estimation technique [7,8]. Since modeling errors and unknown inputs are unavoidable in practical systems and may seriously affect the performance of the FDI system, increasing the robustness to disturbance, while at the same time enhancing the sensitivity to faults, is therefore a critical issue and has been investigated in, see for example [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

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On designing H∞ fault estimator for switched nonlinear systems of neutral type

Liu

Yuan

2011

Communications in Nonlinear Science and Numerical Simulation

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“…si ðR i þ s 2 1 S i ÞA si : In view of Schur complement, (7) implies that X i < 0. Then we have _ V i ðt; n t Þ þ aV i ðt; n t Þ < 0 for all g 1 (t) -0.…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On designing H∞ fault estimator for switched nonlinear systems of neutral type

Liu

Yuan

2011

Communications in Nonlinear Science and Numerical Simulation

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“…Then the faults are diagnosed based on parameter estimation. In [13], least-squares (LSs) parameter estimation method is applied to construct residual generators for a satellite's orbital and attitude model, and the faults are further detected and isolated. In [14][15][16], the subspace identification method for fault diagnosis is proposed, which directly identified a primary form of residual generators instead of the process model.…”

Section: Introductionmentioning

confidence: 99%

Fault diagnosis based on parameter estimation in closed‐loop systems

Zhai

Wang

2015

IET Control Theory & Applications

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In this study, parameter faults in a class of non-identifiable closed-loop multiple-input multiple-output systems are considered. A new parameter estimation-based fault diagnosis method is proposed. It is known that in open-loop systems, the system parameters can be identified directly and the on-line identification results can be used for fault detection and isolation. However, as the closed-loop system is non-identifiable because of the correlation introduced by the controller, unique optimal parameter estimation solution cannot be obtained. To address such an issue, a new method to detect and isolate parameter faults of closed-loop systems without persistent excitation condition is proposed. A reduced-order model is firstly constructed, which is the projection of the original model onto the orthogonal direction of the controller. By doing this, the aforementioned correlation can be successfully removed. The parameters of the newly constructed model, called as feature parameters, are then identified. The physical faults are finally detected and isolated based on the on-line identification results of the feature parameters, the projection direction and the known influence matrix. Simulation results are given to show the effectiveness of the proposed method.

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“…Most popular approaches for fault detection in nonlinear systems are mainly based on nonlinear observers [3,4], on parameter estimation methods [5], on neural network based fault observers [6] or on fuzzy systems based observers [7].…”

Section: Introductionmentioning

confidence: 99%

Actuator fault diagnosis in mechanical systems — Fault power estimation approach

Márton

2014

Int. J. Control Autom. Syst.

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A systematic method is introduced to deal with actuator faults in a class of nonlinear mechanical control systems. The presence of the fault is detected by monitoring the fault induced modifications in the control system's energy balance. From the energy deviation the residual generator estimates the power of the fault. For fault isolation and identification the set of fault power pattern signals is defined. Using signal processing methods the elements of this set are compared to the residual signal to determine the characteristics and the magnitude of the fault. The method does not require assumptions on the system's model and it can handle parameter uncertainties. The applicability of the proposed method is shown through mechatronic examples.

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Parameter Estimation-Based Fault Detection, Isolation and Recovery for Nonlinear Satellite Models

Cited by 110 publications

References 15 publications

On designing H∞ fault estimator for switched nonlinear systems of neutral type

On designing H∞ fault estimator for switched nonlinear systems of neutral type

Fault diagnosis based on parameter estimation in closed‐loop systems

Actuator fault diagnosis in mechanical systems — Fault power estimation approach

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