Two cascaded and extended kalman filters combined with sliding mode control for sustainable management of marine fish stocks
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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Two cascaded and extended kalman filters combined with sliding mode control for sustainable management of marine fish stocks. / Benz, Katharina; Rech, Claus; Mercorelli, Paolo et al.
in: Journal of Automation, Mobile Robotics and Intelligent Systems, Jahrgang 14, Nr. 3, 2020, S. 28-35.Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung › begutachtet
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TY - JOUR
T1 - Two cascaded and extended kalman filters combined with sliding mode control for sustainable management of marine fish stocks
AU - Benz, Katharina
AU - Rech, Claus
AU - Mercorelli, Paolo
AU - Sergiyenko, Oleg
N1 - This work was realised within the lectures for the Complementary Studies course at Leuphana University of Lueneburg during the winter semester 2018- 2019.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Extended Kalman Filter
KW - Lotka‐Volterra Model
KW - Sliding Mode Control
KW - Engineering
UR - http://www.scopus.com/inward/record.url?scp=85100529636&partnerID=8YFLogxK
U2 - 10.14313/JAMRIS/3-2020/30
DO - 10.14313/JAMRIS/3-2020/30
M3 - Journal articles
AN - SCOPUS:85100529636
VL - 14
SP - 28
EP - 35
JO - JAMRIS, Journal of Automation, Mobile Robotics & Intelligent Systems
JF - JAMRIS, Journal of Automation, Mobile Robotics & Intelligent Systems
SN - 1897-8649
IS - 3
ER -