TY - JOUR
T1 - Optimal control of the reaction-diffusion process on directed networks
AU - Liu, Chen
AU - Gao, Shupeng
AU - Song, Mingrui
AU - Bai, Yue
AU - Chang, Lili
AU - Wang, Zhen
N1 - Publisher Copyright:
© 2022 Author(s).
PY - 2022/6/1
Y1 - 2022/6/1
N2 - Reaction-diffusion processes organized in networks have attracted much interest in recent years due to their applications across a wide range of disciplines. As one type of most studied solutions of reaction-diffusion systems, patterns broadly exist and are observed from nature to human society. So far, the theory of pattern formation has made significant advances, among which a novel class of instability, presented as wave patterns, has been found in directed networks. Such wave patterns have been proved fruitful but significantly affected by the underlying network topology, and even small topological perturbations can destroy the patterns. Therefore, methods that can eliminate the influence of network topology changes on wave patterns are needed but remain uncharted. Here, we propose an optimal control framework to steer the system generating target wave patterns regardless of the topological disturbances. Taking the Brusselator model, a widely investigated reaction-diffusion model, as an example, numerical experiments demonstrate our framework's effectiveness and robustness. Moreover, our framework is generally applicable, with minor adjustments, to other systems that differential equations can depict.
AB - Reaction-diffusion processes organized in networks have attracted much interest in recent years due to their applications across a wide range of disciplines. As one type of most studied solutions of reaction-diffusion systems, patterns broadly exist and are observed from nature to human society. So far, the theory of pattern formation has made significant advances, among which a novel class of instability, presented as wave patterns, has been found in directed networks. Such wave patterns have been proved fruitful but significantly affected by the underlying network topology, and even small topological perturbations can destroy the patterns. Therefore, methods that can eliminate the influence of network topology changes on wave patterns are needed but remain uncharted. Here, we propose an optimal control framework to steer the system generating target wave patterns regardless of the topological disturbances. Taking the Brusselator model, a widely investigated reaction-diffusion model, as an example, numerical experiments demonstrate our framework's effectiveness and robustness. Moreover, our framework is generally applicable, with minor adjustments, to other systems that differential equations can depict.
UR - http://www.scopus.com/inward/record.url?scp=85131731109&partnerID=8YFLogxK
U2 - 10.1063/5.0087855
DO - 10.1063/5.0087855
M3 - 文章
C2 - 35778117
AN - SCOPUS:85131731109
SN - 1054-1500
VL - 32
JO - Chaos
JF - Chaos
IS - 6
M1 - 063115
ER -