2,312 publications from this institution
An optimal trajectory planning problem for a single-link, flexible joint manipulator is studied. A global feedback-linearization is first applied to formulate the nonlinear inequality-constrained optimization problem in a suitable way. Then, an exact and explicit structural formula for the optimal solution of the problem is derived and the solution is shown to be unique. It turns out that the optimal trajectory planning and control can be done off-line, so that the proposed method is applicable to both theoretical analysis and real time tele-robotics control engineering.
Recently, it has been demonstrated that many large complex networks display a scale-free feature, that is, their connectivity distributions are in the power-law form. In this paper, we investigate the synchronization phenomenon in scale-free dynamical networks. We show that if the coupling strength of a scale-free dynamical network is greater than a positive threshold, then the network will synchronize no matter how large it is. We show that the synchronizability of a scale-free dynamical network is robust against random removal of nodes, but is fragile to specific removal of the most highly connected nodes.
No abstract is provided for this article.
The basic objective of system modeling is to establish an input-output representative mapping that can satisfactorily describe the system behaviors, by using the available input-output data based upon physical or empirical knowledge about the structure of the unknown system. Request access from your librarian to read this chapter's full text.
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 the present work, control of a scale-free dynamical network by applying local feedback injections to a fraction of network nodes is investigated. The specifically and randomly pinning schemes are considered. The specifically pinning of the most highly connected nodes is shown to require a significantly smaller number of local controllers as compared to the randomly pinning scheme. The method is applied to an array of Chua's oscillators as an example.
Controlling chaos is a new concept, which has drawn much attention from the communities of engineering, physics, chemistry, biomedical sciences, mathematics, and social sciences. This paper offers an overview of different approaches to the control of chaos for various nonlinear dynamic systems. The purpose of presenting this survey is to further promote new efforts devoted to this challenging and promising field of research, as well as its potential applications, in nonlinear systems science and engineering.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
In this paper, the consensus problem is investigated for a class of second-order nonlinear multi-agent systems with intermittent measurements and directed topology. A novel protocol designed based only on the intermittent local feedback is introduced to guarantee the states of multiple agents to converge. By virtue of the Lyapunov control approach, it is theoretically proved that second-order consensus can be achieved exponentially if the general algebraic connectivity and the communication time duration are larger than their corresponding threshold values respectively. Finally, a simulation example is given to verify the theoretical analysis.
In this letter, a new hyperchaotic system is formulated by introducing an additional state into the third-order generalized Lorenz equation. The existence of the hyperchaos is verified with bifurcation analysis, and the bifurcation routes from periodic, quasi-periodic, chaotic and hyperchaotic evolutions are observed. Various attractors are illustrated not only by computer simulation but also by the realization of an electronic circuit. Copyright © 2005 John Wiley & Sons, Ltd.
Small-world networks are highly clustered networks with small distances among the nodes. There are many biological neural networks that present this kind of connections. There are no special weightings in the connections of most existing small-world network models. However, this kind of simply-connected models cannot characterize biological neural networks, in which there are different weights in synaptic connections. In this paper, we present a neural network model with weighted small-world connections, and further investigate the stability of this model.
In this paper, a new approach for synchronization of complex dynamical networks is proposed based on state observer design. Unlike the common diagonally coupling networks, where full state coupling is typically needed between two nodes, here it is suggested that only a scalar coupling signal is required to achieve network synchronization. Some conditions for synchro- nization, in the form of an inequality, are established based on the Lyapunov stability theory, which can be transformed to a linear matrix inequality and easily solved by a numerical toolbox. Two typical dynamical network configurations, i.e., global coupling and nearest-neighbor coupling, with each node being a modified Chua's circuit, are simulated. It is demonstrated that the proposed scheme is effective in achieving the expected chaos synchronization in the complex network. Index Terms—Complex dynamical network, linear matrix in- equality (LMI), Lyapunov stability, state observer, synchroniza- tion.
No abstract is provided for this article.
In this Letter, we study the bifurcation of the Kuramoto–Sivashinsky (K–S) equation in one-spatial dimension with three kinds of boundary value conditions. Using the Liapunov–Schmidt reduction technique, the original equation is first reduced to one or two bifurcation equations, so that bifurcation analysis of the original equation can be transformed to that of the reduced-order systems, and can therefore be carried out in detail.
In the paper “Some Open Problems in Chaos Theory and Dynamics” by Zeraoulia and Sprott, the two-dimensional map [Formula: see text] was considered and the problem on the analytical study of the boundedness of its attractors was formulated. In the present paper, the boundedness of its attractors is studied, the corresponding analytical estimation of absorbing set is obtained, and thus an answer to the problem is given.
In this Letter, an electrical circuit is built for realizing the multi-state intermittency generated by a simple force-driven chaotic system. The intermittency phenomenon and its underlaying mechanism are analyzed, and the experimental results are discussed. It is shown that, with two classes of invariant subspaces, the number of the laminar states and the distance between the adjacent laminar states of the created multi-state on-off intermittency can be arbitrarily changed by manipulating the control parameters.
Liver transplantation (LT) stands as the gold standard for treating end‐stage liver disease and hepatocellular carcinoma, yet postoperative complications continue to impact survival rates. The liver's unique immune system, governed by a microenvironment of diverse immune cells, is disrupted during processes like ischemia–reperfusion injury posttransplantation, leading to immune imbalance, inflammation, and subsequent complications. In the posttransplantation period, immune cells within the liver collaboratively foster a tolerant environment, crucial for immune tolerance and liver regeneration. While clinical trials exploring cell therapy for LT complications exist, a comprehensive summary is lacking. This review provides an insight into the intricacies of the liver's immune microenvironment, with a specific focus on macrophages and T cells as primary immune players. Delving into the immunological dynamics at different stages of LT, we explore the disruptions after LT and subsequent immune responses. Focusing on immune cell targeting for treating liver transplant complications, we provide a comprehensive summary of ongoing clinical trials in this domain, especially cell therapies. Furthermore, we offer innovative treatment strategies that leverage the opportunities and prospects identified in the therapeutic landscape. This review seeks to advance our understanding of LT immunology and steer the development of precise therapies for postoperative complications.
