This paper deals with the convergence of a remote iterative learning control system subject to data dropouts. The system is composed by a set of discrete-time multiple input-multiple output linear models, each one with its corresponding actuator device and its sensor. Each actuator applies the input signals vector to its corresponding model at the sampling instants and the sensor measures the output signals vector. The iterative learning law is processed in a controller located far away of the models so the control signals vector has to be transmitted from the controller to the actuators through transmission channels. Such a law uses the measurements of each model to generate the input vector to be applied to its subsequent model so the measurements of the models have to be transmitted from the sensors to the controller. All transmissions are subject to failures which are described as a binary sequence taking value 1 or 0. A compensation dropout technique is used to replace the lost data in the transmission processes. The convergence to zero of the errors between the output signals vector and a reference one is achieved as the number of models tends to infinity. ; The authors are very grateful to the Spanish Government for its support of this research through Grant DPI2012-30651 and to the Basque Government for its support through Grants IT378-10 and SAIOTEK S-PE12UN015. They are also grateful to the University of the Basque Country for its financial support through Grant UFI 2011/07.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    A Data Dropout Compensation Algorithm Based on the Iterative Learning Control Methodology for Discrete-Time Systems



    Erscheinungsdatum :

    2015-01-01



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



    Data-Driven Iterative Learning Control for Discrete-Time Systems

    Chi, Ronghu / Hui, Yu / Hou, Zhongsheng | TIBKAT | 2022


    Iterative learning control for discrete parabolic distributed parameter systems

    Dai, X. S. / Tian, S. P. / Guo, Y. J. | British Library Online Contents | 2015


    A high-order internal model based iterative learning control scheme for discrete linear time-varying systems

    Zhou, W. / Yu, M. / Huang, D. Q. | British Library Online Contents | 2015


    Iterative Learning Identification with Bias Compensation for Stochastic Linear Time-Varying Systems

    Song, Fazhi / Liu, Yang / Yang, Zhile et al. | Springer Verlag | 2017


    Vehicle Longitudinal Control Algorithm Based on Iterative Learning Control

    Wang, Dazhi / Hu, Hongyu / Wang, Jun et al. | SAE Technical Papers | 2016