The Control of A Non-Linear Chaotic System Using Genetic and Particle Swarm Based On Optimization Algorithms
Journal Title: International Journal of Intelligent Systems and Applications in Engineering - Year 2016, Vol 4, Issue 4
Abstract
In this study, the control of a non-linear system was realized by using a linear system control strategy. According to the strategy and by using the controller coefficients, system outputs were controlled for all reference points with the same coefficients via focused references. In the framework of this study, the Lorenz chaotic system as non-linear structure, and the discrete-time PI algorithm as the control algorithm has selected. The genetic algorithm and particle swarm optimization methods have used in the optimization process, and the success of both methods has been discussed among themselves. Closed-loop control system has run simultaneously under the Matlab / Simulink programmer. The results have discussed by using the ISE, IAE, ITAE error criteria, and improved dTISDSE purpose functions.
Authors and Affiliations
Ercan Kose*| Mechatronic Engineering., Technology Faculty, Mersin University, Mersin, Turkey, Aydin Muhurcu| Electrical and Electronics Engineering, Faculty of Engineering, Sakarya University, Sakarya, Turkey
Keywords
Related Articles
- EP ID EP813
- DOI 10.18201/ijisae.2016426386
- Views 440
- Downloads 25
SLAM – Map Building and Navigation via ROS#
The presented work describes a ROS based control system of a Turtlebot robot for mapping and navigation in indoor environments. It presents the navigation of Turtlebot in self-created environment. The mapping process is...
Classification of Leaf Type Using Artificial Neural Networks
A number of shape features for automatic plant recognition based on digital image processing have been proposed by Pauwels et al. in 2009. Then Silva et al in 2014 have presented database comprises 40 different plant spec...
Statistical Methods for Quantitatively Detecting Fungal Disease from Fruits’ Images
In this paper we have proposed statistical methods for detecting fungal disease and classifying based on disease severity levels. Most fruits diseases are caused by bacteria, fungi, virus, etc of which fungi are respons...
A fuzzy approach for determination of prostate cancer
Goal of this study is a design of a fuzzy expert system, its application aspects in the medicine area and its introduction for calculation of numeric value of prostate cancer risk. For this aim it was used prostate speci...
Speed Control of Direct Torque Controlled Induction Motor By using PI, Anti-Windup PI and Fuzzy Logic Controller
In this study, comparison between PI controller, fuzzy logic controller (FLC) and an anti-windup PI (PI+AW) controller used for speed control with direct torque controlled induction motor is presented. Direct torque cont...