Quantitative fault estimation for a class of non-linear systems

Vijayaraghavan, Krishna; Rajamani, Rajesh; Bokor, József

doi:10.1080/00207170600921029

Cited by 36 publications

(22 citation statements)

References 17 publications

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“…In terms of the above equality and Lemma 1, it is easy to find that (27) holds if the following inequality…”

Section: Resultsmentioning

confidence: 99%

“…In this case, because of the time-varying nature, one would be more interested in the system's transient performances over a finite period than the traditional steady-state behaviors over the infinite-horizon. It should be pointed out that, in comparison with the numerous literature concerning fault estimation problems over the infinite horizon for time-invariant systems [9,16,22,27,32], only scattered results have emerged on the finite-horizon fault estimation problems for time-varying systems. This is not surprising because of the following three identified difficulties for finite-horizon fault estimation problems: 1) how to define a reasonable performance criteria such as H ∞ index to evaluate the reliability of a fault estimator; 2) how to analyze the system performance over a finite horizon; and 3) how to design the fault estimator parameters such that the obtained estimator satisfies the defined estimation performance index.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

H_∞fault estimation with randomly occurring uncertainties, quantization effects and successive packet dropouts: The finite-horizon case

Wang

Ding

et al. 2014

Int. J. Robust. Nonlinear Control

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In this paper, the finite-horizon H ∞ fault estimation problem is investigated for a class of uncertain nonlinear time-varying systems subject to multiple stochastic delays. The randomly occurring uncertainties (ROUs) enter into the system due to the random fluctuations of network conditions. The measured output is quantized by a logarithmic quantizer before being transmitted to the fault estimator. Also, successive packet dropouts (SPDs) happen when the quantized signals are transmitted through an unreliable network medium. Three mutually independent sets of Bernoullidistributed white sequences are introduced to govern the multiple stochastic delays, ROUs and SPDs. By employing the stochastic analysis approach, some sufficient conditions are established for the desired finite-horizon fault estimator to achieve the specified H ∞ performance. The time-varying parameters of the fault estimator are obtained by solving a set of recursive linear matrix inequalities (RLMIs). Finally, an illustrative numerical example is provided to show the effectiveness of the proposed fault estimation approach.

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“…In terms of the above equality and Lemma 1, it is easy to find that (27) holds if the following inequality…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

H_∞fault estimation with randomly occurring uncertainties, quantization effects and successive packet dropouts: The finite-horizon case

Wang

Ding

et al. 2014

Int. J. Robust. Nonlinear Control

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show abstract

“…A simple example of a flexible link robot was used to show the application of the proposed optimization-based methodology. Future work will involve the optimization of the observer sensor FD scheme using partial measurements [6], [18] and assuming multiple sensor faults, as well as the comparison with alternative techniques on fault detectability.…”

Section: Discussionmentioning

confidence: 99%

Optimization of observer design for sensor fault detection of nonlinear systems

Reppa

Timotheou

Polycarpou

2017

2017 IEEE 56th Annual Conference on Decision and Control (CDC)

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Abstract-This paper presents an optimization methodology for the design of an observer-based sensor fault detection scheme for a class of nonlinear systems. Taking into account bounded system disturbances and measurement noise, we design an observer aiming at maximizing the set of faults that are guaranteed to be strongly detectable. Strong fault detectability conditions are derived based on the limit sets that bound the residual under healthy and faulty conditions. A novel optimization method is designed based on the separation of the healthy and faulty limit sets. The distance between these sets represents the trade-off between robustness and sensor fault sensitivity. Simulation results are used to show the effectiveness of the proposed methodology applied to a simple example of a flexible link robot.

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“…Using the Schur complement lemma again, (39) is equivalent to (28), which means that, for all nonzero 1 ( ) ∈ 2 [0, ∞), 2 ( ) ∈ 2 [0, ∞), and Δ ( ) ∈ 2 [0, ∞), one obtains < 0. Therefore, we can conclude from (35) that the ∞ performance criterion (29) is satisfied.…”

Section: Robust Stability Analysis Of the Euler-approximate Proportiomentioning

confidence: 99%

Robust Fault Reconstruction in Discrete-Time Lipschitz Nonlinear Systems via Euler-Approximate Proportional Integral Observers

Jia

Chen

Zhang

et al. 2015

Mathematical Problems in Engineering

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The problem of observer-based robust fault reconstruction for a class of nonlinear sampled-data systems is investigated. A discretetime Lipschitz nonlinear system is first established, and its Euler-approximate model is described; then, an Euler-approximate proportional integral observer (EPIO) is constructed such that simultaneous reconstruction of system states and actuator faults are guaranteed. The presented EPIO possesses the disturbance-decoupling ability because its architecture is similar to that of a nonlinear unknown input observer. The robust stability of the EPIO and convergence of fault-reconstructing errors are proved using Lyapunov stability theory together with ∞ techniques. The design of the EPIO is reformulated into convex optimization problem involving linear matrix inequalities (LMIs) such that its gain matrices can be conveniently calculated using standard LMI tools. In addition, to guarantee the implementation of the EPIO on the exact model, sufficient conditions of its semiglobal practical convergence are provided explicitly. Finally, a single-link flexible robot is employed to verify the effectiveness of the proposed faultreconstructing method.

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Quantitative fault estimation for a class of non-linear systems

Cited by 36 publications

References 17 publications

H_∞fault estimation with randomly occurring uncertainties, quantization effects and successive packet dropouts: The finite-horizon case

H_∞fault estimation with randomly occurring uncertainties, quantization effects and successive packet dropouts: The finite-horizon case

Optimization of observer design for sensor fault detection of nonlinear systems

Robust Fault Reconstruction in Discrete-Time Lipschitz Nonlinear Systems via Euler-Approximate Proportional Integral Observers

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Quantitative fault estimation for a class of non-linear systems

Cited by 36 publications

References 17 publications

H∞fault estimation with randomly occurring uncertainties, quantization effects and successive packet dropouts: The finite-horizon case

H∞fault estimation with randomly occurring uncertainties, quantization effects and successive packet dropouts: The finite-horizon case

Optimization of observer design for sensor fault detection of nonlinear systems

Robust Fault Reconstruction in Discrete-Time Lipschitz Nonlinear Systems via Euler-Approximate Proportional Integral Observers

Contact Info

Product

Resources

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H_∞fault estimation with randomly occurring uncertainties, quantization effects and successive packet dropouts: The finite-horizon case

H_∞fault estimation with randomly occurring uncertainties, quantization effects and successive packet dropouts: The finite-horizon case