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Global exponential stability results for the host-parasitoid model of sugarcane borer in stochastic environment with impulsive effects via non-fragile control: An LMI approach

  • Dianavinnarasi Joseph
  • , Raja Ramachandran
  • , Jehad Alzabut
  • , Jinde Cao
  • , Michal Niezabitowski
  • , Chee Peng Lim
  • Alagappa University
  • Prince Sultan University (PSU)
  • Southeast University, Nanjing
  • Yonsei University
  • Deakin University

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

In this article, we evaluate how the random environmental fluctuations affect the interplay between the sugarcane borer (Diatraea saccharalis) and its egg parasitoid (Trichogramma galloi). In order to procure an optimal control input, we considered the uncertainties in the control agent that leads to a non-fragile control synthesis. Due to the existence of a stochastic environment and uncertainties in the control agent, the impulsive biological control is introduced to stabilize the situation. By means of the classical Lyapunov method, a new sufficient condition for exponential stability of our proposed population model through non-fragile control and impulsive biological control is established. With the assistance of linear matrix inequality (LMI) solvers, non-fragile controllers can be obtained effortlessly. In addition, we provide simulation studies that are primarily based on the sugarcane borer system to demonstrate the effectiveness and benefits of our proposed model.

Original languageEnglish
Pages (from-to)512-531
Number of pages20
JournalOptimal Control Applications and Methods
Volume43
Issue number2
DOIs
Publication statusPublished - 1 Mar 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger

Keywords

  • actuator fault
  • egg parasitoid
  • flex fuel
  • impulsive pest control
  • mathematical modeling
  • non-fragile control
  • stochastic environment
  • sugarcane borer

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Control and Optimization
  • Applied Mathematics

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