In this brief, we propose a method to optimize the topology of networks to enhance their pinning controllability while the locations of the drivers and their associated feedback gains are fixed. Inspired by the master stability function approach, pinning controllability is measured by the eigenratio of the augmented Laplacian matrix. A perturbation mechanism is used to approximate the influence of adding or removing edges on pinning controllability, which leads to a criterion for efficient rewirings. Simulation results on model scale-free networks show that the proposed rewiring-based topology optimization strategy can successfully optimize pinning controllability. The optimized networks show significantly different topological properties as compared with the original networks. Furthermore, regardless of the initial choice of drivers, they become hubs in the optimized networks.
['Mahdi Jalili', 'Xinghuo Yu']
Enhancing Pinning Controllability of Complex Networks Through Link Rewiring