TY  - JOUR
A1  - Gout, Julien
A1  - Quade, Markus
A1  - Shafi, Kamran
A1  - Niven, Robert K.
A1  - Abel, Markus
T1  - Synchronization control of oscillator networks using symbolic regression
T2  - Nonlinear Dynamics
N2  - Networks of coupled dynamical systems provide a powerful way to model systems with enormously complex dynamics, such as the human brain. Control of synchronization in such networked systems has far-reaching applications in many domains, including engineering and medicine. In this paper, we formulate the synchronization control in dynamical systems as an optimization problem and present a multi-objective genetic programming-based approach to infer optimal control functions that drive the system from a synchronized to a non-synchronized state and vice versa. The genetic programming-based controller allows learning optimal control functions in an interpretable symbolic form. The effectiveness of the proposed approach is demonstrated in controlling synchronization in coupled oscillator systems linked in networks of increasing order complexity, ranging from a simple coupled oscillator system to a hierarchical network of coupled oscillators. The results show that the proposed method can learn highly effective and interpretable control functions for such systems.
KW  - Dynamical systems
KW  - Synchronization control
KW  - Genetic programming
Y1  - 2017
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/54268
SN  - 0924-090X
SN  - 1573-269X
VL  - 91
IS  - 2
SP  - 1001
EP  - 1021
PB  - Springer
CY  - Dordrecht
ER  -