Skip to main content

Published Article - September 2012, Volume 1, Number 1

Published Article - September 2012, Volume 1, Number 1

Paper Title:

HYBRID SYNCHRONIZATION OF HYPERCHAOTIC LIU SYSTEMS VIA SLIDING MODE CONTROL

Authors:

Sundarapandian Vaidyanathan1

1Research and Development Centre, Vel Tech Dr. RR & Dr. SR Technical University Avadi, Chennai-600 062, Tamil Nadu, INDIA 

ABSTRACT

This paper derives new results for the hybrid synchronization of identical hyperchaotic Liu systems (Liu, Liu and Zhang, 2008) via sliding mode control. In hybrid synchronization of master and slave systems, the odd states of the two systems are completely synchronized, while their even states are antisynchronized. The stability results derived in this paper for the hybrid synchronization of identical hyperchaotic Liu systems have been proved using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the sliding mode control method is very effective and convenient to achieve anti- synchronization of the identical hyperchaotic Liu systems. Numerical simulations are shown to illustrate and validate the hybrid synchronization schemes derived in this paper for the identical hyperchaotic Liu systems. 

KEYWORDS

Distributed real-time embedded system (DRE), reliability assessment, average case system behaviour testing, Monte-Carlo simulation.

Volume URL: https://airccse.org/journal/ijccms/current.html

Full Text: https://airccse.org/journal/ijccms/papers/1112ijccms01.pdf





Comments

Post a Comment

Popular posts from this blog

Comparison of Support Vector Machines and Deep Learning for Plant Classification in Smart Agriculture Applications

Comparison of Support Vector Machines and Deep Learning for Plant Classification in Smart Agriculture Applications Authors Esmael Hamuda 1, Ashkan Parsi 2, Martin Glavin 2 and Edward Jones 2, 1 Elmergib University, Libya, 2 University of Galway, Ireland Abstract In this paper, we investigate the use of deep learning approaches for plant classification (cauliflower and weeds) in smart agriculture applications. To perform this, five approaches were considered, two based on well-known deep learning architectures (AlexNet and GoogleNet), and three based on Support Vector Machine (SVM) classifiers with different feature sets (Bag of Words in L*a*b colour space, Bag of Words in HSV colour space, Bag of Words of Speeded-up Robust Features (SURF)). Two types of datasets were used in this study: one without Data Augmentation and the second one with Data Augmentation. Each algorithm's performance was tested with one data set similar to the training data, and a second data set acquired under ...
Post a Comment
Read more
SEASONAL VARIATION OF CARRYING CAPACITY ON DISEASED MODEL CAN CAUSE SPECIES EXTINCTION Prodip Roy1, Banshidhar Sahoo2, and Swarup Poria3 1,2,3 Department of Mathematics, Mahadevananda Mahavidyalaya, Kolkata-120, India. ABSTRACT Most natural populations experience fluctuations in biological and environmental factors which causes carrying capacity variation. In this paper, we have introduced a diseased prey-predator model with periodically varying carrying capacity. We have studied the effects of different amplitudes of oscillation as well as different frequencies of oscillation on the dynamics of the model. We have done bifurcation analysis of the model with respect to the amplitude of oscillation and frequency of oscillation of the carrying capacity. We observe limit cycle, low periodic orbits, high periodic orbits and chaos in the model. We observe the existence of critical frequency and amplitude of oscillation of carrying capacity for which the prey population ex...
Post a Comment
Read more

PERFORMANCE COMPARISON OF TWO CONTROLLERS ON A NONLINEAR SYSTEM

PERFORMANCE COMPARISON OF TWO CONTROLLERS ON A NONLINEAR SYSTEM Kenneth O.M. Mapoka, Dr Tranos Zuva2, Howard Masebu3 and Keneilwe Zuva4 1Department of Agricultural Engineering and Land Planning, Botswana College of Agriculture, Gaborone, Botswana ABSTRACT Various systems and instrumentation use auto-tuning techniques in their operations. For example, audio processors, designed to control pitch in vocal and instrumental operations. The main aim of autotuning is to conceal off-key errors and allowing artists to perform genuinely despite slight deviation off-key. In this paper two, Auto tuning control strategies are proposed. These are Proportional, Integral and Derivative (PID) control and Model Predictive Control (MPC). The PID and MPC controller’s algorithms amalgamate the auto-tuning method. These control strategies ascertain stability, effective and efficient performance on a nonlinear system. The paper test and compare the efficacy of each control strategy. This paper gen...
Post a Comment
Read more