Control design using genetic optimized pole placement

Authors:
Cornel Rentea
Affiliations:
Department of Automation and Computer Science, University "Lucian Blaga" Sibiu, Sibiu, Romania
Venue:
ICAI'05/MCBC'05/AMTA'05/MCBE'05 Proceedings of the 6th WSEAS international conference on Automation & information, and 6th WSEAS international conference on mathematics and computers in biology and chemistry, and 6th WSEAS international conference on acoustics and music: theory and applications, and 6th WSEAS international conference on Mathematics and computers in business and economics
Year:
2005

Citing 6
Cited 0

Application of a general learning algorithm to the control of robotic manipulators

International Journal of Robotics Research
Genetic programming: on the programming of computers by means of natural selection

Genetic programming: on the programming of computers by means of natural selection
MATLAB tools for control system analysis and design

MATLAB tools for control system analysis and design
Automatic control systems (7th ed.)

Automatic control systems (7th ed.)
Multivariable Feedback Design

Multivariable Feedback Design
Feedback Control of Dynamic Systems

Feedback Control of Dynamic Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, in order to improve pole placement design performance we used a genetic algorithm to help choosing the control parameters and so effectively and efficiently optimize the performance of the controller. We discuss this optimization of a pole placement control design for the Inverted Pendulum problem, considered an acknowledged benchmark in nonlinear system control.