I was not expecting President Barack Obama to mention science and technology in his inaugural speech. But he actually did. When he promised to "restore science to its rightful place, and wield technology's wonders to raise health-care's quality and lower its cost," I was impressed. British Prime Minister Gordon Brown echoed, in his address to the University of Oxford on February 27, 2009, that science is a key element to Britain's recovery from the economic downturn; therefore, he would not let science become "a victim of the recession."
An approach for studying typical point-to-point trajectory tracking problems for nonlinear control systems that possess a global linearization is proposed. The trajectory constraints include both the inequality and the equality (interpolatory) types. For purposes of theoretical analysis, system-behavior understanding, and controller design, a minimum control-energy criterion for the linearized system is used. Under this optimality criterion, a characterization result for describing all the possible solutions of such trajectory tracking problems is established. Moreover, the general structure is found in explicit closed-form for these solutions. The research is motivated by a specific example of robotic trajectory planning. Some computer simulation graphs on the robotic trajectory planning problem are included.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
This work proposes a practical approach to applying more complex perturbations into a liquid mixing process by using sampled output signals from a chaotic circuit. The mixing process in one of the most widely utilized mixing devices, the stirred tank, is considered. A motor-driven liquid mixer based on the stirred tank model is designed and implemented for carrying out intensive experiments. Different signals, such as DC signals, sinusoidal wave signals and chaotic signals, have been tested for driving the motor, which produces the intended motion perturbations, including constant, periodic and chaotic motion patterns. Analysis on different outcomes under several mixing conditions gives some sensible relationships between the motion perturbation patterns and the liquid mixing efficiency, showing the superiority of chaotic perturbations over the others. Chaotic signals are considered the best choice for achieving mixing efficiency from a practical point of view, when they are properly used for controlling the liquid mixers.
This paper presents a new approach to implement the dynamic reconfigurable logical systems based on Cellular Neural Networks (CNN), comparing with utilizing the chaos computing system, which is easier to implement in engineering applications and more stable. We provided and experimentally demonstrated the basic principle for obtaining a full-adder by using uncoupled CNN cells. The actual circuit to implementing the full-adder and transforming from adder to subtractor also has been presented.
Recently, it has been demonstrated that many large complex networks display a scale-free feature, that is, their connectivity distributions have the power-law form. In this paper, we investigate the synchronization phenomena in a scale-free dynamical network. We show that its synchronizability is robust against random removal of nodes, but is fragile to specific removal of the most highly connected nodes.
In this paper, the problem of making a nonlinear system chaotic by using state-feedback control is studied, where the feedback controller uses a simple sine function of the system state with only one single component in each dimension. It is proved that the designed control system generates chaos in the sense of Li and Yorke.
This Letter suggests a new approach to generating chaos via dynamic neural networks. This approach is based on a recently introduced methodology of inverse optimal control for nonlinear systems. Both Chen's chaotic system and Chua's circuit are used as examples for demonstration. The control law is derived to force a dynamic neural network to reproduce the intended chaotic attractors. Computer simulations are included for illustration and verification.
We present a time-delayed SIS model on complex networks to study epidemic spreading. We found that the existence of delay will affect, and oftentimes enhance, both outbreak and prevalence of infectious diseases in the networks. For small-world networks, we found that the epidemic threshold and the delay time have a power-law relation. For scale-free networks, we found that for a given transmission rate, the epidemic prevalence has an exponential form, which can be analytically obtained, and it decays as the delay time increases. We confirm all results by sufficient numerical simulations.
No abstract is provided for this article.
This paper reports a class of chaotic attractors with toroidal or spherical patterns. These attractors look like spheres or tori, but they are not exactly on the two-dimensional toroidal/spherical surfaces. Discontinuous structures are taken in the considered system to produce easily various chaotic tori/spheres with different input functions. Moreover, controlling the shape of these chaotic attractors can be realized by adjusting some parameters with the help of Fourier series. The underlying chaos-generation mechanism is also explored briefly.
