2,312 publications from this institution
Scientific Committee: Nicholas Alikakos, Peter Bates(Chair), Yongluo Cao, Guanrong Chen, Sui Sun Cheng, Shui-Nee Chow(Co-chair), L.O. Chua, Xilin Fu, Giorgio Fusco, Bolin Guo, Lihong Huang, Wenzhang Huang, Jifa Jiang, Christopher Jones, Tibor Krisztin, Chengzhi Li, Jia Li, Weigu Li, Yong Li, Xiao-Biao Lin, Bing Liu, Weishi Liu, Kening Lu, Zhien Ma, Dingbian Qian, Shigui Ruan, Wenxian Shen, Junping Shi, Yuefei Wang, Junjie Wei, Lan Wen, Jianhong Wu, Zhihong Xia, Dongmei Xiao, Daoyi Xu, Yuantong Xu, Xiangdong Ye, Yingfei Yi, Jiangong You, Rong Yuan, Xiaoping Yuan, Chongchun Zeng, Meirong Zhang, Weinian Zhang, Xiang Zhang, Xiaoqiang Zhao, Shengfan Zhou, Deming Zhu, Huaiping Zhu, Xingfu Zou
This article investigates some subtle characteristics of stability and bifurcation of the chaotic Chen’s system, based on rigorous mathematical analysis and symbolic computations.
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No abstract is provided for this article.
No abstract is provided for this article.
This paper provides a suboptimal solution to the problem of automatically back-driving a truck using the natural parabolic paths as the shortest moving distance requirement. By applying fuzzy logic control techniques, a controller with nine rules is developed, which works well even without using a mathematical system model. As long as the states (position and orientation) of the truck are measurable at each discrete-time step during the control process, this controller can drive the truck to follow any feasible trajectories (their smallest radii are no less than the smallest radius of the curve along which the truck can travel), and to move successfully into a prescribed parking lot. In addition to the design of the controller, controllability and stability of the control system are briefly discussed under the condition that only partial information about the current states of the system are available. Simulation results are presented, to demonstrate the accuracy and effectiveness of this new fuzzy logic controller and to compare its control performance with other fuzzy logic controllers that were designed for the same purpose under the same conditions but without using any optimality criterion.
A computational aspect of real-time estimation is considered, in which the estimation algorithm to be used has the standard optimal Kalman filtering structure, but the actual inverse matrix within the Kalman gain is replaced by an expedient approximation at each instant. In real-time applications, most Kalman filtering schemes are approximate to a degree as a consequence of numerical roundoff matrix inversion. The convergence properties and error estimates of such schemes are obtained to provide a theoretical basis for gauging the utility of using the above approximations of the Kalman gain matrix at each time instant. A new exponentially convergent scheme is also suggested for approximating the inverse matrix within the Kalman gain. Conditions are determined under which online approximate matrix inversion can be eliminated as the cause of Kalman filter divergence in real-time implementations.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
In this paper, decentralised fixed modes (DFMs) of a networked system are studied. The network topology is directed and weighted and the nodes are higher-dimensional linear time-invariant (LTI) dynamical systems. The effects of the network topology, the node-system dynamics, the external control inputs, and the inner interactions on the existence of DFMs for the whole networked system are investigated. A necessary and sufficient condition for networked multi-input/multi-output (MIMO) systems in a general topology to possess no DFMs is derived. For networked single-input/single-output (SISO) LTI systems in general as well as some typical topologies, some specific conditions for having no DFMs are established. It is shown that the existence of DFMs is an integrated result of the aforementioned relevant factors which cannot be decoupled into individual DFMs of the node-systems and the properties solely determined by the network topology.
In this paper, the important issue of Laplacian eigenvalue distributions is investigated through theory-guided extensive numerical simulations, for four typical complex network models, namely, the ER random-graph networks, WS and NW small-world networks, and BA scale-free networks. It is found that these four types of complex networks share some common features, particularly similarities between the Laplacian eigenvalue distributions and the node degree distributions.
Random walks constitute a fundamental mechanism for a large set of dynamics taking place on networks. In this article, we study random walks on weighted networks with an arbitrary degree distribution, where the weight of an edge between two nodes has a tunable parameter. By using the spectral graph theory, we derive analytical expressions for the stationary distribution, mean first-passage time (MFPT), average trapping time (ATT), and lower bound of the ATT, which is defined as the average MFPT to a given node over every starting point chosen from the stationary distribution. All these results depend on the weight parameter, indicating a significant role of network weights on random walks. For the case of uncorrelated networks, we provide explicit formulas for the stationary distribution as well as ATT. Particularly, for uncorrelated scale-free networks, when the target is placed on a node with the highest degree, we show that ATT can display various scalings of network size, depending also on the same parameter. Our findings could pave a way to delicately controlling random-walk dynamics on complex networks.
A quasi-analytical approach is developed for detecting period-doubling bifurcation emerging near a Hopf bifurcation point. The new algorithm employs higher-order Harmonic Balance Approximations (HBAs) to compute the monodromy matrix, useful for the study of limit cycle bifurcations. Prediction of the period-doubling bifurcation is accomplished very accurately by using this algorithm, along with a detailed approximation error analysis, without using numerical integration of the dynamical system. An example is given to illustrate the results.
Cooperative traffic systems renew much research interest with the rapid development of communication technologies. This paper considers a finite number of vehicles moving in a single lane from a mesoscale perspective and explores the spectral properties of such a cooperative system, in particular how the communication range and the coupling weights influence the eigenvalues of the global disturbance transition matrix (DTM), i.e., disturbance modes of the traffic system. Dynamics of these vehicles are described by a modified coupled-map car-following model under periodic boundaries with inter-vehicle communications. From a state-space approach, a system DTM is established from a global view and a closed-form solution of its eigenvalues is derived. Linear stability conditions are subsequently obtained. It is found that the eigenvalue distribution of system DTM is essentially dominated by the communication range and the coupling weights, but nearly independent of the system size. By analyzing the magnitudes of the dominant poles, the synchronization of the traffic system is enhanced if the weights of the vehicles within the communication range are more evenly distributed or the communication range is increased. Particularly, it is shown that the optimal communication network tends to be a mean-field network w.r.t. global synchronization, indicating that a communication network emphasizing uniform importance among vehicles within each vehicle’s communication range is helpful for improving the synchronizability. Finally, numerical simulations verify the results.
In this paper, we investigate a networked prisoner's dilemma game where individuals' strategy-selection time scale evolves based on their historical learning information. We show that the more times the current strategy of an individual is learnt by his neighbors, the longer time he will stick on the successful behavior by adaptively adjusting the lifetime of the adopted strategy. Through characterizing the extent of success of the individuals with normalized payoffs, we show that properly using the learned information can form a positive feedback mechanism between cooperative behavior and its lifetime, which can boost cooperation on square lattices and scale-free networks.
In this paper, the problem of making a stable map chaotic by using smooth small-amplitude high-frequency feedback control is studied. The controlled map is mathematically proven to be chaotic in the sense of Li and Yorke. To demonstrate the practical usefulness of the proposed method, it is applied to a feedback boost switching regulator model operating in discontinuous mode. Copyright © 2000 John Wiley & Sons, Ltd.
This paper describes a proportional-differential (PD) control algorithm as a new active queue management (AQM) scheme for TCP/IP congestion control. From the viewpoint of the control theory, TCP congestion control system can be regarded as a feedback regulating system. In this paper, a robust AQM called PD-controller is proposed. The design principles of PD-controller are presented in details. Its performance is extensively evaluated by simulations. The results demonstrate that the PD-controller AQM is stable and robust against traffic load fluctuations, UDP and HTTP disturbances. Its superiority over other AQMs is also demonstrated.
