An adaptive observer design methodology for bounded nonlinear processes

Hovakimyan, Naira; Calise, Anthony J.; Madyastha, Venkatesh

doi:10.1109/cdc.2002.1185120

Cited by 33 publications

(19 citation statements)

References 14 publications

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“…However, for interval coefficients there is a significant difference between the formulas. Equation (8) provides better bounds for the values compared to those which would have been obtained in the point-by-point procedure, because C i02;j+1 1 C i01;1 C i01;1 Ci02;j+1: (9) Second, and more significantly, in calculating C i;j by (8) use fixed values of C i02;1 and C i01;1 instead of their intervals. The fixed values may be the midpoints of the intervals or, if desired, the values which yield the largest intervals for Ci;j .…”

Section: Modification Of the Methods Of Direct Truncation Of Routmentioning

confidence: 97%

On routh-pade model reduction of interval systems

Dolgin

Zeheb

2003

IEEE Trans. Automat. Contr.

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Section: Modification Of the Methods Of Direct Truncation Of Routmentioning

confidence: 97%

On routh-pade model reduction of interval systems

Dolgin

Zeheb

2003

IEEE Trans. Automat. Contr.

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“…where is a bounded disturbance [26], i.e., for a positive constant , due to the bounded characteristic of the sigmoidal function.…”

Section: B Stability Analysismentioning

confidence: 99%

A Neural Network-Based Multiplicative Actuator Fault Detection and Isolation of Nonlinear Systems

Talebi

Khorasani

2013

IEEE Trans. Contr. Syst. Technol.

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The problem of fault detection and isolation/identification (FDI) of nonlinear systems using neural networks is considered in this paper. The proposed FDI approach employs recurrent neural network-based observers for simultaneously detecting, isolating and identifying the severity of actuator faults in presence of disturbances and uncertainties in the model and sensory measurements. The neural network weights are updated based on a modified dynamic backpropagation scheme. The proposed FDI scheme does not rely on the availability of full state measurements. In most works in the literature the fault function acts as an additive term on the actuator, whereas in this work the fault acts as a multiplicative term. This will make the formal stability and convergence analysis of the overall FDI scheme nontrivial and challenging. Our stability analysis considers the presence of plant and sensor uncertainties through the use of Lyapunov's direct method with no restrictive assumptions on the system and/or the FDI algorithm. The performance of our proposed FDI approach is evaluated through simulations that are performed for two case studies, namely FDI of 1) reaction wheel type actuators that are commonly utilized in the attitude control subsystem (ACS) of a satellite and 2) actuators in a two-link flexible joint manipulator.Index Terms-Fault detection and isolation, multiplicative actuator faults, nonlinear systems, recurrent neural networks.

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“…It has been shown that the state estimation error converges to zero only if the disturbances vanish. In [15], the disturbances are assumed to be generated by an exponentially stable system, such that observability of the combined system is not violated.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Observer Design for Uncertain Systems With Bounded Disturbances

Stepanyan

Hovakimyan

2007

IEEE Trans. Neural Netw.

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This paper presents a robust adaptive observer design methodology for a class of uncertain nonlinear systems in the presence of time-varying unknown parameters with absolutely integrable derivatives, and nonvanishing disturbances. Using the universal approximation property of radial basis function (RBF) neural networks and the adaptive bounding technique, the developed observer achieves asymptotic convergence of state estimation error to zero, while ensuring boundedness of parameter errors. A comparative simulation study is presented by the end.

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An adaptive observer design methodology for bounded nonlinear processes

Cited by 33 publications

References 14 publications

On routh-pade model reduction of interval systems

On routh-pade model reduction of interval systems

A Neural Network-Based Multiplicative Actuator Fault Detection and Isolation of Nonlinear Systems

Robust Adaptive Observer Design for Uncertain Systems With Bounded Disturbances

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