This paper deals with a possible approach to controlling marine fish stocks using the prey‐predator model described by the Lotka‐Volterra equations. The control strategy is conceived using the sliding mode control (SMC) approach which, based on the Lyapunov theorem, offers the possibility to track desired functions, thus guaranteeing the stability of the controlled system. One of the most important aspects of this model is the identification of some parameters which characterizes the model. In this work two cascaded and Extended Kalman Filters (EKFs) are proposed to estimate them in order to be utilized in SMC. This approach can be used for sustainable management of marine fish stocks: through the developed algorithm, the appropriate number of active fishermen and the suitable period for fishing can be determined. Computer simulations validate the proposed approach.


    Access

    Download


    Export, share and cite



    Title :

    Two cascaded and extended kalman filters combined with sliding mode control for sustainable management of marine fish stocks


    Contributors:

    Publication date :

    2020-01-01


    Remarks:

    Benz , K , Rech , C , Mercorelli , P & Sergiyenko , O 2020 , ' Two cascaded and extended kalman filters combined with sliding mode control for sustainable management of marine fish stocks ' , Journal of Automation, Mobile Robotics and Intelligent Systems , vol. 14 , no. 3 , pp. 28-35 . https://doi.org/10.14313/JAMRIS/3-2020/30



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



    Suboptimality of Cascaded and Federated Kalman Filters

    Levy, L. / Institute of Navigation | British Library Conference Proceedings | 1996


    Cascaded Dual Extended Kalman Filter for Combined Vehicle State Estimation and Parameter Identification

    Rezaeian, A. / Zarringhalam, R. / Fallah, S. et al. | British Library Conference Proceedings | 2013


    Cascaded Dual Extended Kalman Filter for Combined Vehicle State Estimation and Parameter Identification

    Khajepour, Amir / Rezaeian, Ayyoub / Litkouhi, Baktiarr et al. | SAE Technical Papers | 2013


    Limits in tracking with extended Kalman filters

    Schlosser, M.S. / Kroschel, K. | IEEE | 2004

    Free access