%0 Journal Article
%T Linear Dynamic Controllers Evolved by Genetic Regulatory Network Based Artificial Cells
%A Navid Rahbari Asr
%A Vahid Johari Majd
%A Majid Hassan Zadeh Shojai
%A Mehdi Behnam
%J International Journal of Machine Learning and Computing
%D 2013
%I IACSIT Press
%R 10.7763/ijmlc.2013.v3.269
%X In this paper a linear representation of a synthetic genetic regulatory network (GRN) model is derived and it is used for evolving linear dynamic controllers for nonlinear systems. A case study is considered in which running the genetic algorithm on the elements of the system matrix of a linear controller is unable to evolve and reach the control ends, while running the genetic algorithm on the genes of an artificial cell with linear regulatory networks evolves and a linear controller is achieved. This justifies the computational burden imposed on computations due to GRN dynamics as GRN representation increases the evolvability of the controller.
%K Genetic regulatory networks
%K linear artificial cells
%K linear dynamic controller
%K genetic algorithms
%K evolvability.
%U http://www.ijmlc.org/index.php?m=content&c=index&a=show&catid=35&id=266