Recently, we have proposed a new probabilistic method for the control of chaotic systems [1]. In this paper, we apply our method to characteristic cases of chaotic maps (one- and two-dimensional examples). As these chaotic maps are structurally stable, they cannot be controlled using conventional control methods without significant change of the dynamics. Our method consists in the probabilistic coupling of the original system with a controlling system. This coupling can be understood as a feedback control of probabilistic nature. The chosen periodic orbit of the original system is a global attractor for the probability densities. The generalized spectral decomposition of the associated Frobenius-Perron operator provides a spectral conditio...
We discuss the characterization of chaotic behaviors in random maps both in terms of the Lyapunov ex...
This book offers a short and concise introduction to the many facets of chaos theory. While the stud...
AbstractWe define and calculate the probability density in phase space and the information entropy o...
AbstractRecently, we have proposed a new probabilistic method for the control of chaotic systems [1]...
We propose a new, probabilistic, approach for the control of chaotic systems. This approach is illus...
2003Some important ideas froni classical control theory are introduced with the intention of applyin...
We derive an absolute condition for probabilistic control [Antoniou et al. 1996] of the unstable dyn...
Chaos is a kind of nonlinear system response that has a dense set of unstable periodic orbits (UPOs)...
AbstractAn algorithm is proposed whereby any chaotic transformation τ (i.e., one merely possessing a...
Abstract – A chaos control method suggested by Erjaee has been reviewed. It has been shown that this...
The Inverse Frobenius-Perron problem (IFPP) concerns the creation of discrete chaotic mappings with ...
Chaos is a typical phenomenon in nonlinear dynamical systems. Until recently, the extreme sensitivit...
When a probabilistic description of deterministic chaos is feasible, it can describe the dynamical e...
In this paper, we give a review of the Inverse Frobenius–Perron problem (IFPP): how to create chaot...
Abstract — When strong multiplicative noise is added to a dynamical system, we find two distinct gen...
We discuss the characterization of chaotic behaviors in random maps both in terms of the Lyapunov ex...
This book offers a short and concise introduction to the many facets of chaos theory. While the stud...
AbstractWe define and calculate the probability density in phase space and the information entropy o...
AbstractRecently, we have proposed a new probabilistic method for the control of chaotic systems [1]...
We propose a new, probabilistic, approach for the control of chaotic systems. This approach is illus...
2003Some important ideas froni classical control theory are introduced with the intention of applyin...
We derive an absolute condition for probabilistic control [Antoniou et al. 1996] of the unstable dyn...
Chaos is a kind of nonlinear system response that has a dense set of unstable periodic orbits (UPOs)...
AbstractAn algorithm is proposed whereby any chaotic transformation τ (i.e., one merely possessing a...
Abstract – A chaos control method suggested by Erjaee has been reviewed. It has been shown that this...
The Inverse Frobenius-Perron problem (IFPP) concerns the creation of discrete chaotic mappings with ...
Chaos is a typical phenomenon in nonlinear dynamical systems. Until recently, the extreme sensitivit...
When a probabilistic description of deterministic chaos is feasible, it can describe the dynamical e...
In this paper, we give a review of the Inverse Frobenius–Perron problem (IFPP): how to create chaot...
Abstract — When strong multiplicative noise is added to a dynamical system, we find two distinct gen...
We discuss the characterization of chaotic behaviors in random maps both in terms of the Lyapunov ex...
This book offers a short and concise introduction to the many facets of chaos theory. While the stud...
AbstractWe define and calculate the probability density in phase space and the information entropy o...