The Experts below are selected from a list of 9735 Experts worldwide ranked by ideXlab platform

R. Filipiak - One of the best experts on this subject based on the ideXlab platform.

  • application of time frequency analysis to the evaluation of the condition of Car Suspension
    Mechanical Systems and Signal Processing, 2015
    Co-Authors: Grzegorz Szymański, Marian Jósko, Franciszek Tomaszewski, R. Filipiak
    Abstract:

    Abstract The article presents possibilities of use of vibration signal parameters for the evaluation of elements׳ clearance in the Car Suspension system. The time-spectrum analysis has been proposed to determine the frequency band connected with Car body free vibration generated by impacts of Suspension elements in case of clearance in Suspension elements fixing to the Car body. Diagnostic models allowing evaluation of shock absorber fastening to the Car body are described in this work.

  • Application of time–frequency analysis to the evaluation of the condition of Car Suspension
    Mechanical Systems and Signal Processing, 2015
    Co-Authors: Grzegorz Szymański, Marian Jósko, Franciszek Tomaszewski, R. Filipiak
    Abstract:

    Abstract The article presents possibilities of use of vibration signal parameters for the evaluation of elements׳ clearance in the Car Suspension system. The time-spectrum analysis has been proposed to determine the frequency band connected with Car body free vibration generated by impacts of Suspension elements in case of clearance in Suspension elements fixing to the Car body. Diagnostic models allowing evaluation of shock absorber fastening to the Car body are described in this work.

Fuwen Yang - One of the best experts on this subject based on the ideXlab platform.

  • event triggered h_ infty state estimation of 2 dof quarter Car Suspension systems with nonhomogeneous markov switching
    IEEE Transactions on Systems Man and Cybernetics, 2020
    Co-Authors: Huaicheng Yan, Hao Zhang, Jiayu Sun, Xi-sheng Zhan, Fuwen Yang
    Abstract:

    In this paper, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is investigated for a two-degree-of-freedom quarter-Car Suspension system operated over a switching-channel network environment. First, the channel-switching is governed by a nonhomogeneous Markov chain whose probability transition matrix is time-varying. Then, a Markov jump linear system model is adopted to represent the overall networked system in view of the event-triggered communication scheme, signal quantization and random packet losses on account of the limited network bandwidth. By virtue of the Lyapunov functional and linear matrix inequality method, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is transformed into an optimization problem that switching-channel-dependent estimators are designed such that the estimation error system is exponentially stable in the mean square sense and achieves a desired performance level. Finally, a simulation example is used to demonstrate the validity of proposed design method.

  • Event-Triggered $H_\infty$ State Estimation of 2-DOF Quarter-Car Suspension Systems With Nonhomogeneous Markov Switching
    IEEE Transactions on Systems Man and Cybernetics: Systems, 2020
    Co-Authors: Huaicheng Yan, Hao Zhang, Jiayu Sun, Xi-sheng Zhan, Fuwen Yang
    Abstract:

    In this paper, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is investigated for a two-degree-of-freedom quarter-Car Suspension system operated over a switching-channel network environment. First, the channel-switching is governed by a nonhomogeneous Markov chain whose probability transition matrix is time-varying. Then, a Markov jump linear system model is adopted to represent the overall networked system in view of the event-triggered communication scheme, signal quantization and random packet losses on account of the limited network bandwidth. By virtue of the Lyapunov functional and linear matrix inequality method, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is transformed into an optimization problem that switching-channel-dependent estimators are designed such that the estimation error system is exponentially stable in the mean square sense and achieves a desired performance level. Finally, a simulation example is used to demonstrate the validity of proposed design method.

  • event based distributed h_ infty filtering networks of 2 dof quarter Car Suspension systems
    IEEE Transactions on Industrial Informatics, 2017
    Co-Authors: Hao Zhang, Qianqian Hong, Huaicheng Yan, Fuwen Yang, Ge Guo
    Abstract:

    This paper is concerned with the problem of vertical attitude estimation of a two-degree-of-freedom quarter-Car Suspension system by designing a distributed filtering network, where several distributed filters estimate vehicle heave motion cooperatively under consideration of external disturbance, network channel noises, and measurement error. The sampled data are transmitted through wireless networks. In order to reduce network traffic load and save communication resources, a novel periodic event-triggered sampling scheme is proposed, under which data are transmitted only when the proposed triggering condition is violated. Codesign of event-triggered and distributed filters is derived to guarantee well $H_{\infty }$ robustness to the system noises considered above. Finally, the experiments are given to show the effectiveness of the proposed filtering system.

  • Event-Based Distributed $H_{\infty }$ Filtering Networks of 2-DOF Quarter-Car Suspension Systems
    IEEE Transactions on Industrial Informatics, 2017
    Co-Authors: Hao Zhang, Qianqian Hong, Huaicheng Yan, Fuwen Yang, Ge Guo
    Abstract:

    This paper is concerned with the problem of vertical attitude estimation of a two-degree-of-freedom quarter-Car Suspension system by designing a distributed filtering network, where several distributed filters estimate vehicle heave motion cooperatively under consideration of external disturbance, network channel noises, and measurement error. The sampled data are transmitted through wireless networks. In order to reduce network traffic load and save communication resources, a novel periodic event-triggered sampling scheme is proposed, under which data are transmitted only when the proposed triggering condition is violated. Codesign of event-triggered and distributed filters is derived to guarantee well $H_{\infty }$ robustness to the system noises considered above. Finally, the experiments are given to show the effectiveness of the proposed filtering system.

Hao Zhang - One of the best experts on this subject based on the ideXlab platform.

  • event triggered h_ infty state estimation of 2 dof quarter Car Suspension systems with nonhomogeneous markov switching
    IEEE Transactions on Systems Man and Cybernetics, 2020
    Co-Authors: Huaicheng Yan, Hao Zhang, Jiayu Sun, Xi-sheng Zhan, Fuwen Yang
    Abstract:

    In this paper, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is investigated for a two-degree-of-freedom quarter-Car Suspension system operated over a switching-channel network environment. First, the channel-switching is governed by a nonhomogeneous Markov chain whose probability transition matrix is time-varying. Then, a Markov jump linear system model is adopted to represent the overall networked system in view of the event-triggered communication scheme, signal quantization and random packet losses on account of the limited network bandwidth. By virtue of the Lyapunov functional and linear matrix inequality method, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is transformed into an optimization problem that switching-channel-dependent estimators are designed such that the estimation error system is exponentially stable in the mean square sense and achieves a desired performance level. Finally, a simulation example is used to demonstrate the validity of proposed design method.

  • Event-Triggered $H_\infty$ State Estimation of 2-DOF Quarter-Car Suspension Systems With Nonhomogeneous Markov Switching
    IEEE Transactions on Systems Man and Cybernetics: Systems, 2020
    Co-Authors: Huaicheng Yan, Hao Zhang, Jiayu Sun, Xi-sheng Zhan, Fuwen Yang
    Abstract:

    In this paper, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is investigated for a two-degree-of-freedom quarter-Car Suspension system operated over a switching-channel network environment. First, the channel-switching is governed by a nonhomogeneous Markov chain whose probability transition matrix is time-varying. Then, a Markov jump linear system model is adopted to represent the overall networked system in view of the event-triggered communication scheme, signal quantization and random packet losses on account of the limited network bandwidth. By virtue of the Lyapunov functional and linear matrix inequality method, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is transformed into an optimization problem that switching-channel-dependent estimators are designed such that the estimation error system is exponentially stable in the mean square sense and achieves a desired performance level. Finally, a simulation example is used to demonstrate the validity of proposed design method.

  • event based distributed h_ infty filtering networks of 2 dof quarter Car Suspension systems
    IEEE Transactions on Industrial Informatics, 2017
    Co-Authors: Hao Zhang, Qianqian Hong, Huaicheng Yan, Fuwen Yang, Ge Guo
    Abstract:

    This paper is concerned with the problem of vertical attitude estimation of a two-degree-of-freedom quarter-Car Suspension system by designing a distributed filtering network, where several distributed filters estimate vehicle heave motion cooperatively under consideration of external disturbance, network channel noises, and measurement error. The sampled data are transmitted through wireless networks. In order to reduce network traffic load and save communication resources, a novel periodic event-triggered sampling scheme is proposed, under which data are transmitted only when the proposed triggering condition is violated. Codesign of event-triggered and distributed filters is derived to guarantee well $H_{\infty }$ robustness to the system noises considered above. Finally, the experiments are given to show the effectiveness of the proposed filtering system.

  • Event-Based Distributed $H_{\infty }$ Filtering Networks of 2-DOF Quarter-Car Suspension Systems
    IEEE Transactions on Industrial Informatics, 2017
    Co-Authors: Hao Zhang, Qianqian Hong, Huaicheng Yan, Fuwen Yang, Ge Guo
    Abstract:

    This paper is concerned with the problem of vertical attitude estimation of a two-degree-of-freedom quarter-Car Suspension system by designing a distributed filtering network, where several distributed filters estimate vehicle heave motion cooperatively under consideration of external disturbance, network channel noises, and measurement error. The sampled data are transmitted through wireless networks. In order to reduce network traffic load and save communication resources, a novel periodic event-triggered sampling scheme is proposed, under which data are transmitted only when the proposed triggering condition is violated. Codesign of event-triggered and distributed filters is derived to guarantee well $H_{\infty }$ robustness to the system noises considered above. Finally, the experiments are given to show the effectiveness of the proposed filtering system.

Grzegorz Szymański - One of the best experts on this subject based on the ideXlab platform.

  • application of time frequency analysis to the evaluation of the condition of Car Suspension
    Mechanical Systems and Signal Processing, 2015
    Co-Authors: Grzegorz Szymański, Marian Jósko, Franciszek Tomaszewski, R. Filipiak
    Abstract:

    Abstract The article presents possibilities of use of vibration signal parameters for the evaluation of elements׳ clearance in the Car Suspension system. The time-spectrum analysis has been proposed to determine the frequency band connected with Car body free vibration generated by impacts of Suspension elements in case of clearance in Suspension elements fixing to the Car body. Diagnostic models allowing evaluation of shock absorber fastening to the Car body are described in this work.

  • Application of time–frequency analysis to the evaluation of the condition of Car Suspension
    Mechanical Systems and Signal Processing, 2015
    Co-Authors: Grzegorz Szymański, Marian Jósko, Franciszek Tomaszewski, R. Filipiak
    Abstract:

    Abstract The article presents possibilities of use of vibration signal parameters for the evaluation of elements׳ clearance in the Car Suspension system. The time-spectrum analysis has been proposed to determine the frequency band connected with Car body free vibration generated by impacts of Suspension elements in case of clearance in Suspension elements fixing to the Car body. Diagnostic models allowing evaluation of shock absorber fastening to the Car body are described in this work.

Huaicheng Yan - One of the best experts on this subject based on the ideXlab platform.

  • event triggered h_ infty state estimation of 2 dof quarter Car Suspension systems with nonhomogeneous markov switching
    IEEE Transactions on Systems Man and Cybernetics, 2020
    Co-Authors: Huaicheng Yan, Hao Zhang, Jiayu Sun, Xi-sheng Zhan, Fuwen Yang
    Abstract:

    In this paper, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is investigated for a two-degree-of-freedom quarter-Car Suspension system operated over a switching-channel network environment. First, the channel-switching is governed by a nonhomogeneous Markov chain whose probability transition matrix is time-varying. Then, a Markov jump linear system model is adopted to represent the overall networked system in view of the event-triggered communication scheme, signal quantization and random packet losses on account of the limited network bandwidth. By virtue of the Lyapunov functional and linear matrix inequality method, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is transformed into an optimization problem that switching-channel-dependent estimators are designed such that the estimation error system is exponentially stable in the mean square sense and achieves a desired performance level. Finally, a simulation example is used to demonstrate the validity of proposed design method.

  • Event-Triggered $H_\infty$ State Estimation of 2-DOF Quarter-Car Suspension Systems With Nonhomogeneous Markov Switching
    IEEE Transactions on Systems Man and Cybernetics: Systems, 2020
    Co-Authors: Huaicheng Yan, Hao Zhang, Jiayu Sun, Xi-sheng Zhan, Fuwen Yang
    Abstract:

    In this paper, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is investigated for a two-degree-of-freedom quarter-Car Suspension system operated over a switching-channel network environment. First, the channel-switching is governed by a nonhomogeneous Markov chain whose probability transition matrix is time-varying. Then, a Markov jump linear system model is adopted to represent the overall networked system in view of the event-triggered communication scheme, signal quantization and random packet losses on account of the limited network bandwidth. By virtue of the Lyapunov functional and linear matrix inequality method, the event-triggered $\boldsymbol {H}_{\boldsymbol \infty }$ state estimation problem is transformed into an optimization problem that switching-channel-dependent estimators are designed such that the estimation error system is exponentially stable in the mean square sense and achieves a desired performance level. Finally, a simulation example is used to demonstrate the validity of proposed design method.

  • event based distributed h_ infty filtering networks of 2 dof quarter Car Suspension systems
    IEEE Transactions on Industrial Informatics, 2017
    Co-Authors: Hao Zhang, Qianqian Hong, Huaicheng Yan, Fuwen Yang, Ge Guo
    Abstract:

    This paper is concerned with the problem of vertical attitude estimation of a two-degree-of-freedom quarter-Car Suspension system by designing a distributed filtering network, where several distributed filters estimate vehicle heave motion cooperatively under consideration of external disturbance, network channel noises, and measurement error. The sampled data are transmitted through wireless networks. In order to reduce network traffic load and save communication resources, a novel periodic event-triggered sampling scheme is proposed, under which data are transmitted only when the proposed triggering condition is violated. Codesign of event-triggered and distributed filters is derived to guarantee well $H_{\infty }$ robustness to the system noises considered above. Finally, the experiments are given to show the effectiveness of the proposed filtering system.

  • Event-Based Distributed $H_{\infty }$ Filtering Networks of 2-DOF Quarter-Car Suspension Systems
    IEEE Transactions on Industrial Informatics, 2017
    Co-Authors: Hao Zhang, Qianqian Hong, Huaicheng Yan, Fuwen Yang, Ge Guo
    Abstract:

    This paper is concerned with the problem of vertical attitude estimation of a two-degree-of-freedom quarter-Car Suspension system by designing a distributed filtering network, where several distributed filters estimate vehicle heave motion cooperatively under consideration of external disturbance, network channel noises, and measurement error. The sampled data are transmitted through wireless networks. In order to reduce network traffic load and save communication resources, a novel periodic event-triggered sampling scheme is proposed, under which data are transmitted only when the proposed triggering condition is violated. Codesign of event-triggered and distributed filters is derived to guarantee well $H_{\infty }$ robustness to the system noises considered above. Finally, the experiments are given to show the effectiveness of the proposed filtering system.