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ASU Scholarship Showcase

This growing collection consists of scholarly works authored by ASU-affiliated faculty, students and community members, and contains many open access articles. ASU-affiliated authors are encouraged to Share Your Work in the ASU Digital Repository.

In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains an outstanding problem. Here we develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another, assuming that the former is undesired and the latter is desired. To make our framework practically meaningful, we consider restricted parameter perturbation by imposing two constraints: it must be experimentally realizable and applied only temporarily. We introduce the concept of attractor network, which allows us to …

Wang, Le-Zhi, Su, Riqi, Huang, Zi-Gang, et al.
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