The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform

Cong Wang - One of the best experts on this subject based on the ideXlab platform.

  • Fault Diagnosis for a Class of Sampled-data Systems via Deterministic Learning
    2019 Chinese Control And Decision Conference (CCDC), 2019
    Co-Authors: Shaoyan Wang, Tianrui Chen, Cong Wang
    Abstract:

    In this paper, an approach for rapid detection of Small Oscillation faults for a class of sampled-data nonlinear system is proposed based on deterministic learning theory. Firstly, based on the Euler approximate discrete time model of the continuous-time system, a training estimator is constructed to learn the normal mode and the fault modes. By using the deterministic learning theory and stability results of linear discrete time-varying systems, the modeling uncertainty and the fault functions are locally-accurately approximated. The obtained knowledge are stored in constant RBF networks. Secondly, by utilizing learned knowledge, a set of estimators are constructed. One estimator represents the normal mode, whereas the others represent the fault modes. The average L1 norms of the residuals are taken as the measure of the differences of dynamics between the monitored system and the estimators. The occurrence of a Oscillation fault can be rapidly detected according to the Smallest residual principle. Simulation study is included to demonstrate the effectiveness of the approach.

  • Rapid fault isolation for a class of nonlinear lipschitz systems via deterministic learning
    2017 29th Chinese Control And Decision Conference (CCDC), 2017
    Co-Authors: Tianrui Chen, Cong Wang
    Abstract:

    Early isolation of Small faults is an important issue in the literature of fault diagnosis. In this paper, for a class of nonlinear lipschitz systems with output measurements, an approach for rapid isolation of Small Oscillation faults is presented. By utilizing the knowledge obtained through the deterministic learning, a bank of estimators is constructed for the training normal mode and Oscillation faults. The occurrence of a fault can be isolated if all the residual norms associated with the matched fault estimator become Smaller than the ones associated with the other estimators in a finite time. Finally, based on the concept of fault mismatched function, rigorous analysis of the performance of the isolation schemes is given. The attractions of the paper lie in that the sensitivity to Small faults is enhanced through using the learned knowledge of modeling uncertainty and nonlinear faults with output measurements.

  • Small Oscillation fault detection for a class of nonlinear systems with output measurements using deterministic learning
    Systems & Control Letters, 2015
    Co-Authors: Tianrui Chen, Cong Wang, David J Hill
    Abstract:

    Abstract Early detection of Small faults is an important issue in the literature of fault diagnosis. In this paper, for a class of nonlinear systems with output measurements, an approach for rapid detection of Small Oscillation faults is presented. Firstly, locally accurate approximations of unknown system dynamics and fault functions are achieved by combining a high gain observer and a deterministic learning (DL) theory. The obtained knowledge of system dynamics for both normal and fault modes is stored in constant RBF networks. Secondly, a bank of dynamical estimators are constructed for all the normal mode and Oscillation faults. The knowledge obtained through DL is reused with a nonhigh-gain design. The occurrence of a fault can be detected if one of residual norms of a fault estimator becomes Smaller than that of the normal estimator in a finite time. A rigorous analysis of the detectability properties of the proposed fault detection scheme is also given, which includes the fault detectability condition and the fault detection time. The attractions of the paper lie in that with output measurements, the knowledge of modeling uncertainty and nonlinear faults is obtained and then is utilized to enhance the sensitivity to Small faults.

  • rapid isolation of Small Oscillation faults via deterministic learning
    International Journal of Adaptive Control and Signal Processing, 2014
    Co-Authors: Tianrui Chen, Cong Wang
    Abstract:

    SUMMARY In this paper, we investigate the Small fault isolation problem for a class of nonlinear uncertain systems. First, by utilizing the learned knowledge obtained through a recently proposed deterministic learning (DL) approach, a bank of estimators is constructed to represent the training normal mode and Oscillation faults. Second, two isolation schemes based on the norms of the residuals are provided. The occurrence of a fault can be isolated if all the norms of the residuals associated with the matched fault estimator become Smaller than the ones of the residuals associated with the other estimators in a finite time. Rigorous analysis of the performance of the both isolation schemes is also given, which includes the fault isolability condition and isolation time. The attraction of the paper lies in that an approach for fault isolation is proposed, in which the knowledge of modeling uncertainty and nonlinear faults obtained through DL is utilized to enhance the sensitivity of the isolation scheme. Simulation studies are included to demonstrate the effectiveness of the approach. Copyright © 2012 John Wiley & Sons, Ltd.

  • Rapid isolation of Small Oscillation faults via deterministic learning
    The 2012 International Joint Conference on Neural Networks (IJCNN), 2012
    Co-Authors: Tianrui Chen, Cong Wang
    Abstract:

    In this paper, we investigate the Small fault isolation problem for a class of nonlinear uncertain systems. First, by utilizing the learned knowledge obtained through a recently proposed deterministic learning (DL) approach, a bank of estimators is constructed to represent the training normal mode and Oscillation faults. Second, two isolation schemes based on the norms of residuals are provided. The occurrence of a fault can be isolated according to Smallest residual principle. Rigorous analysis of the performance of the both isolation schemes is also given. The attraction of the paper lies in that an approach for fault isolation is proposed, in which the knowledge of modeling uncertainty and nonlinear faults obtained through DL is utilized to enhance the sensitivity of the isolation scheme. Simulation studies are included to demonstrate the effectiveness of the approach.

Tianrui Chen - One of the best experts on this subject based on the ideXlab platform.

  • Fault Diagnosis for a Class of Sampled-data Systems via Deterministic Learning
    2019 Chinese Control And Decision Conference (CCDC), 2019
    Co-Authors: Shaoyan Wang, Tianrui Chen, Cong Wang
    Abstract:

    In this paper, an approach for rapid detection of Small Oscillation faults for a class of sampled-data nonlinear system is proposed based on deterministic learning theory. Firstly, based on the Euler approximate discrete time model of the continuous-time system, a training estimator is constructed to learn the normal mode and the fault modes. By using the deterministic learning theory and stability results of linear discrete time-varying systems, the modeling uncertainty and the fault functions are locally-accurately approximated. The obtained knowledge are stored in constant RBF networks. Secondly, by utilizing learned knowledge, a set of estimators are constructed. One estimator represents the normal mode, whereas the others represent the fault modes. The average L1 norms of the residuals are taken as the measure of the differences of dynamics between the monitored system and the estimators. The occurrence of a Oscillation fault can be rapidly detected according to the Smallest residual principle. Simulation study is included to demonstrate the effectiveness of the approach.

  • Rapid fault isolation for a class of nonlinear lipschitz systems via deterministic learning
    2017 29th Chinese Control And Decision Conference (CCDC), 2017
    Co-Authors: Tianrui Chen, Cong Wang
    Abstract:

    Early isolation of Small faults is an important issue in the literature of fault diagnosis. In this paper, for a class of nonlinear lipschitz systems with output measurements, an approach for rapid isolation of Small Oscillation faults is presented. By utilizing the knowledge obtained through the deterministic learning, a bank of estimators is constructed for the training normal mode and Oscillation faults. The occurrence of a fault can be isolated if all the residual norms associated with the matched fault estimator become Smaller than the ones associated with the other estimators in a finite time. Finally, based on the concept of fault mismatched function, rigorous analysis of the performance of the isolation schemes is given. The attractions of the paper lie in that the sensitivity to Small faults is enhanced through using the learned knowledge of modeling uncertainty and nonlinear faults with output measurements.

  • Small Oscillation fault detection for a class of nonlinear systems with output measurements using deterministic learning
    Systems & Control Letters, 2015
    Co-Authors: Tianrui Chen, Cong Wang, David J Hill
    Abstract:

    Abstract Early detection of Small faults is an important issue in the literature of fault diagnosis. In this paper, for a class of nonlinear systems with output measurements, an approach for rapid detection of Small Oscillation faults is presented. Firstly, locally accurate approximations of unknown system dynamics and fault functions are achieved by combining a high gain observer and a deterministic learning (DL) theory. The obtained knowledge of system dynamics for both normal and fault modes is stored in constant RBF networks. Secondly, a bank of dynamical estimators are constructed for all the normal mode and Oscillation faults. The knowledge obtained through DL is reused with a nonhigh-gain design. The occurrence of a fault can be detected if one of residual norms of a fault estimator becomes Smaller than that of the normal estimator in a finite time. A rigorous analysis of the detectability properties of the proposed fault detection scheme is also given, which includes the fault detectability condition and the fault detection time. The attractions of the paper lie in that with output measurements, the knowledge of modeling uncertainty and nonlinear faults is obtained and then is utilized to enhance the sensitivity to Small faults.

  • rapid isolation of Small Oscillation faults via deterministic learning
    International Journal of Adaptive Control and Signal Processing, 2014
    Co-Authors: Tianrui Chen, Cong Wang
    Abstract:

    SUMMARY In this paper, we investigate the Small fault isolation problem for a class of nonlinear uncertain systems. First, by utilizing the learned knowledge obtained through a recently proposed deterministic learning (DL) approach, a bank of estimators is constructed to represent the training normal mode and Oscillation faults. Second, two isolation schemes based on the norms of the residuals are provided. The occurrence of a fault can be isolated if all the norms of the residuals associated with the matched fault estimator become Smaller than the ones of the residuals associated with the other estimators in a finite time. Rigorous analysis of the performance of the both isolation schemes is also given, which includes the fault isolability condition and isolation time. The attraction of the paper lies in that an approach for fault isolation is proposed, in which the knowledge of modeling uncertainty and nonlinear faults obtained through DL is utilized to enhance the sensitivity of the isolation scheme. Simulation studies are included to demonstrate the effectiveness of the approach. Copyright © 2012 John Wiley & Sons, Ltd.

  • Rapid isolation of Small Oscillation faults via deterministic learning
    The 2012 International Joint Conference on Neural Networks (IJCNN), 2012
    Co-Authors: Tianrui Chen, Cong Wang
    Abstract:

    In this paper, we investigate the Small fault isolation problem for a class of nonlinear uncertain systems. First, by utilizing the learned knowledge obtained through a recently proposed deterministic learning (DL) approach, a bank of estimators is constructed to represent the training normal mode and Oscillation faults. Second, two isolation schemes based on the norms of residuals are provided. The occurrence of a fault can be isolated according to Smallest residual principle. Rigorous analysis of the performance of the both isolation schemes is also given. The attraction of the paper lies in that an approach for fault isolation is proposed, in which the knowledge of modeling uncertainty and nonlinear faults obtained through DL is utilized to enhance the sensitivity of the isolation scheme. Simulation studies are included to demonstrate the effectiveness of the approach.

John Tichy - One of the best experts on this subject based on the ideXlab platform.

  • Limits of linearity in squeeze film behavior of a single degree of freedom microsystem
    Microfluidics and Nanofluidics, 2014
    Co-Authors: Shujuan Huang, Diana-andra Borca-tasciuc, John Tichy
    Abstract:

    This paper presents a theoretical investigation of squeeze film flow in systems employing microplates parallel to a substrate and undergoing large amplitude normal vibration. Most previous models of squeeze film damping assume Small Oscillation amplitude with linear system behavior, but it is often unclear how Small the vibrations must be to actually elicit this response. In addition, fluid inertia effects are usually overlooked. This study provides a compact nonlinear solution for the incompressible hydrodynamic forces with specific terms describing fluid inertia and viscous damping. Numerical analysis (the explicit Runge-Kutta method) is applied to solve the nonlinear governing equation. The effects of frequency, Oscillation amplitude, aspect ratio (of gap to length), and Reynolds number on the dynamic response of the system are investigated. The overall system response depends strongly on the actuation frequency and system properties. It is found that a simple criterion of validity for the linear system assumption is not possible. Near resonance, the vibration input amplitude (relative to the initial gap) must be very Small indeed for linearity (∼0.001), while in other cases the relative amplitude can be greater than one.

  • a simple expression for fluid inertia force acting on micro plates undergoing squeeze film damping
    Proceedings of The Royal Society A: Mathematical Physical and Engineering Sciences, 2011
    Co-Authors: Shujuan Huang, Dianaandra Borcatasciuc, John Tichy
    Abstract:

    Squeeze film damping in systems employing micro-plates parallel to a substrate and undergoing Small normal vibrations is theoretically investigated. In high-density fluids, inertia forces may play a significant role affecting the dynamic response of such systems. Previous models of squeeze film damping taking inertia into account do not clearly isolate this effect from viscous damping. Therefore, currently, there is no simple way to distinguish between these two hydrodynamic effects. This paper presents a simple solution for the hydrodynamic force acting on a plate vibrating in an incompressible fluid, with distinctive terms describing inertia and viscous damping. Similar to the damping constant describing viscous losses, an inertia constant, given by ρL 3 W / h (where ρ is fluid density, L and W are plate length and width, respectively, and h is separation distance), may be used to accurately calculate fluid inertia for Small Oscillation Reynolds numbers. In contrast with viscous forces that suppress the amplitude of the Oscillation, it is found that fluid inertia acts as an added mass, shifting the natural frequency of the system to a lower range while having little effect on the amplitude. Dimensionless parameters describing the relative importance of viscous and inertia effects also emerge from the analysis.

Ricardo H Nochetto - One of the best experts on this subject based on the ideXlab platform.

Shujuan Huang - One of the best experts on this subject based on the ideXlab platform.

  • Limits of linearity in squeeze film behavior of a single degree of freedom microsystem
    Microfluidics and Nanofluidics, 2014
    Co-Authors: Shujuan Huang, Diana-andra Borca-tasciuc, John Tichy
    Abstract:

    This paper presents a theoretical investigation of squeeze film flow in systems employing microplates parallel to a substrate and undergoing large amplitude normal vibration. Most previous models of squeeze film damping assume Small Oscillation amplitude with linear system behavior, but it is often unclear how Small the vibrations must be to actually elicit this response. In addition, fluid inertia effects are usually overlooked. This study provides a compact nonlinear solution for the incompressible hydrodynamic forces with specific terms describing fluid inertia and viscous damping. Numerical analysis (the explicit Runge-Kutta method) is applied to solve the nonlinear governing equation. The effects of frequency, Oscillation amplitude, aspect ratio (of gap to length), and Reynolds number on the dynamic response of the system are investigated. The overall system response depends strongly on the actuation frequency and system properties. It is found that a simple criterion of validity for the linear system assumption is not possible. Near resonance, the vibration input amplitude (relative to the initial gap) must be very Small indeed for linearity (∼0.001), while in other cases the relative amplitude can be greater than one.

  • a simple expression for fluid inertia force acting on micro plates undergoing squeeze film damping
    Proceedings of The Royal Society A: Mathematical Physical and Engineering Sciences, 2011
    Co-Authors: Shujuan Huang, Dianaandra Borcatasciuc, John Tichy
    Abstract:

    Squeeze film damping in systems employing micro-plates parallel to a substrate and undergoing Small normal vibrations is theoretically investigated. In high-density fluids, inertia forces may play a significant role affecting the dynamic response of such systems. Previous models of squeeze film damping taking inertia into account do not clearly isolate this effect from viscous damping. Therefore, currently, there is no simple way to distinguish between these two hydrodynamic effects. This paper presents a simple solution for the hydrodynamic force acting on a plate vibrating in an incompressible fluid, with distinctive terms describing inertia and viscous damping. Similar to the damping constant describing viscous losses, an inertia constant, given by ρL 3 W / h (where ρ is fluid density, L and W are plate length and width, respectively, and h is separation distance), may be used to accurately calculate fluid inertia for Small Oscillation Reynolds numbers. In contrast with viscous forces that suppress the amplitude of the Oscillation, it is found that fluid inertia acts as an added mass, shifting the natural frequency of the system to a lower range while having little effect on the amplitude. Dimensionless parameters describing the relative importance of viscous and inertia effects also emerge from the analysis.