A New Unconstrained Optimization Method based on Feedback Control System

In this paper, a control system with optimization calculation ability is presented, in which neural networks is used as the controller and the cost function is used as the control plant. Thus some characters of the control system, such as perturbation or chaos in this system, can help us to find the...

Full description

Saved in:
Bibliographic Details
Published in2007 IEEE International Conference on Control and Automation pp. 2474 - 2478
Main Authors Baiquan Lu, Zhou Jian Zheng, Yuan Min Jie
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2007
Subjects
Ant colony optimization
Automatic control
Automation
Chaos
component
Control system
Control systems
Cost function
Feedback control
Global Optimization
Neural networks
Optimization methods
Perturbation
Simulated annealing
Online AccessGet full text

Cover

More Information
Summary:In this paper, a control system with optimization calculation ability is presented, in which neural networks is used as the controller and the cost function is used as the control plant. Thus some characters of the control system, such as perturbation or chaos in this system, can help us to find the global optimization solution since usual BP control algorithm is very easy to fall into a local minimum point. When a perturbation is added at input side of the controller or there exists chaos in this system, it is possible that its trajectory escapes from a local minimum point to other places for finding global minimum point; in the way until the global minimum point is got. Carrying on some simulations, as a result, it indicates that the optimization method based on the control system is useful for finding global optimization solution of unconstrained optimization problems.
ISBN:9781424408177
1424408172
ISSN:1948-3449
1948-3457
DOI:10.1109/ICCA.2007.4376807