Control and Sensor Node Selection for Nonlinear Systems and Networks

1. Control Node Selection Algorithm for Nonlinear Dynamic Networks

We have developed a novel algorithm for control node selection for nonlinear networks. Our work has been accepted to IEEE Control Systems Letters (August 2020). The link to the paper is given here:

The codes are posted here: https://github.com/AleksandarHaber/Control-Node-Selection-and-Control-Action-Design-for-Nonlinear-Networks-and-Systems

The complete citation is:

Control Node Selection Algorithm for Nonlinear Dynamic Networks, A. Haber, S. A. Nugroho, P. Torres, and A. F. Taha, accepted to IEEE Control Systems Letters, August 2020.

Abstract: The coupled problems of selecting control nodes
and designing control actions for nonlinear network dynamics
are fundamental scientific problems with applications in many
diverse fields. These problems are thoroughly studied for linear
dynamics; however, in spite of a number of open research
questions, methods for nonlinear network dynamics are less
developed. As pointed out by various authors, the prevailing
graph-based controllability approaches for selecting control
nodes might result in far from optimal control performance
for nonlinear dynamics. Herein we present a new, intuitive,
and simple method for simultaneous control node selection and
control sequence design for complex networks with nonlinear
dynamics. The method is developed by incorporating the control
node selection problem into an open-loop predictive control cost
function and by solving the resulting mixed-integer optimization
problem using a mesh adaptive direct search method. The
developed framework is numerically robust and can deal with
stiff networks, networks with non-smooth dynamics, as well
as with control and actuator constraints. Good numerical
performance of the method is demonstrated by testing it on prototypical
Duffing oscillator and associative memory networks.
The developed codes that can easily be adapted to models of
other complex systems are available online.