Paper Info
Title
Suboptimal nonlinear feedback control laws for collective dynamics
Abstract
We present feedback control methodologies for the stabilization of nonlinear collective dynamics. The proposed controllers circumvent the curse of dimensionality associated to dynamic programming of large-scale nonlinear dynamics by means of different structural assumptions on the nonlinearity and the associated Hamilton-Jacobi-Bellman equation. We explore a power series expansion method, and a state-dependent Riccati equation approach. The proposed designs are studied for a relaxed optimal power flow model, and for binary interactions arising in opinion and consensus dynamics.
Year
DOI
Venue
2018
10.1109/ICCA.2018.8444303
2018 IEEE 14th International Conference on Control and Automation (ICCA)
Keywords
Field
DocType
suboptimal nonlinear feedback control laws,nonlinear collective dynamics,power series expansion method,state-dependent Riccati equation approach,relaxed optimal power flow model,consensus dynamics,Hamilton-Jacobi-Bellman equation,stabilization,curse of dimensionality,nonlinearity,large-scale nonlinear dynamics,dynamic programming
Dynamic programming,Nonlinear system,Power flow,Control theory,Curse of dimensionality,Riccati equation,Engineering,Power series,Binary number,Consensus dynamics
Conference
ISSN
ISBN
Citations 
1948-3449
978-1-5386-6090-4
0
PageRank 
References 
Authors
0.34
10
2
Name
Order
Citations
PageRank
Michael Herty123947.31
Dante Kalise2539.15