Controlling Neimark–Sacker bifurcations in discrete-time multivariable systems

D’Amico, María Belén; Chen, Guanrong; Paolini, Eduardo E.; Moiola, Jorge L.

doi:10.1016/j.sysconle.2009.01.002

Cited by 4 publications

(1 citation statement)

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“…In this case, traditional linear control theory is inadequate since the model is uncontrollable around the origin [Vaccaro, 1995]. Different bifurcation control techniques based on the use of time delays, polynomial functions, washout filters, etc., could be used to stabilize the trivial equilibrium [D'Amico et al, 2009;D'Amico & Calandrini, 2015;Franco & Liz, 2013;Huang et al, 2017;Wang et al, 2014]. The proposed strategy arises from the idea of dynamic cancellation, prioritizing fundamentally its simple and intuitive agronomic implementation.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Different Management Strategies for Annual Ryegrass (Lolium rigidum) Based on a Population Dynamic Model

D’Amico

Calandrini

González‐Andújar

et al. 2018

Int. J. Bifurcation Chaos

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Weed species present high competitive capacity, rapid adaptability and herbicide resistance, hindering their effective control across worldwide cropping regions. Since field-conducted experiments are very time-consuming and usually expensive, mathematical population-based models are valuable tools to test and develop long-term weed management programs. Within this context, the objective of this paper is to formalize analytically the possible seed bank dynamics of the Lolium rigidum, subjected to different control strategies. The first focus is on studying in detail the effects of integrating constant actions, promoting more environmentally and economically sustainable scenarios. From the same perspective, an alternative to applying time-variant programs is introduced. The proposed control guarantees that the weed population is sufficiently small or, alternatively, is kept below a given economic threshold level in a ten-year planning horizon. Furthermore, an optimization criterion is adopted for distributing necessary efficiency into diverse integrated options. Numerical simulations are included to illustrate the analytical findings.

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