This paper addresses the consensus problem of multiagent systems with a time-invariant communication topology consisting of general linear node dynamics. A distributed observer-type consensus protocol based on relative output measurements is proposed. A new framework is introduced to address in a unified way the consensus of multiagent systems and the synchronization of complex networks. Under this framework, the consensus of multiagent systems with a communication topology having a spanning tree can be cast into the stability of a set of matrices of the same low dimension. The notion of consensus region is then introduced and analyzed. It is shown that there exists an observer-type protocol solving the consensus problem and meanwhile yielding an unbounded consensus region if and only if each agent is both stabilizable and detectable. A multistep consensus protocol design procedure is further presented. The consensus with respect to a time-varying state and the robustness of the consensus protocol to external disturbances are finally discussed. The effectiveness of the theoretical results is demonstrated through numerical simulations, with an application to low-Earth-orbit satellite formation flying.
This article briefly introduces the generalized Lorenz systems family, which includes the classical Lorenz system and the relatively new Chen system as special cases, with infinitely many related but not topologically equivalent chaotic systems in between.
We present a global payoff-based strategy updating model for studying cooperative behavior of a networked population. We adopt the Prisoner's Dilemma game and the snowdrift game as paradigms for characterizing the interactions among individuals. We investigate the model on regular, small-world, and scale-free networks, and find multistable cooperation states depending on the initial cooperator density. In particular for the snowdrift game on small-world and scale-free networks, there exist a discontinuous phase transition and hysteresis loops of cooperator density. We explain the observed properties by theoretical predictions and simulation results of the average number of neighbors of cooperators and defectors, respectively. Our work indicates that individuals with more neighbors have a trend to preserve their initial strategies, which has strong impacts on the strategy updating of individuals with fewer neighbors; while the fact that individuals with few neighbors have to become cooperators to avoid gaining the lowest payoff plays significant roles in maintaining and spreading of cooperation strategy.
Naming game is a simulation-based experiment used to study the evolution of languages. The conventional naming game focuses on a single language. In this paper, a novel naming game model named multi-language naming game (MLNG) is proposed, where the agents are different-language speakers who cannot communicate with each other without a translator (interpreter) in between. The MLNG model is general, capable of managing k different languages with k ≥ 2. For illustration, the paper only discusses the MLNG with two different languages, and studies five representative network topologies, namely random-graph, WS small-world, NW small-world, scale-free, and random-triangle topologies. Simulation and analysis results both show that: 1) using the network features and based on the proportion of translators the probability of establishing a conversation between two or three agents can be theoretically estimated; 2) the relationship between the convergence speed and the proportion of translators has a power-law-like relation; 3) different agents require different memory sizes, thus a local memory allocation rule is recommended for saving memory resources. The new model and new findings should be useful for further studies of naming games and for better understanding of languages evolution from a dynamical network perspective.
Many systems existing in physics, chemistry, biology, engineering, and information science can be characterized by impulsive dynamics caused by abrupt jumps at certain instants during the process. These complex dynamical behaviors can be modeled by impulsive differential systems or impulsive neural networks. This paper formulates and studies a new model of impulsive autoassociative neural networks. Several fundamental issues, such as global exponential stability and existence and uniqueness of equilibria of such neural networks, are established.
Aiming at the unavoidable consistency difference among cells in an energy storage battery pack, a multi-threshold adaptive clustering group equalization control method is proposed. First, a single-inductor energy storage equalization topology with simple structure, simple control and perfect balancing function is introduced. Second, while introducing the idea of cluster equalization, a group equalization control method is established based on adjacent cells with small consistency difference, so as to realize the transfer of equalization energy between battery groups containing different numbers of adjacent cells. Final, through simulation experiments, it is verified that the proposed cluster group equalization control can significantly improve the equalization speed while ensuring the equalization efficiency compared with the "one-to-one" equalization control based on the extreme difference or average.
Fuzzy control strategy offers an alternative approach for many conventional control systems, which has certain advantages over the other techniques. For example, the improved PI fuzzy controller we designed in this paper, which is based on an existing fuzzy PI controller, can control an uncertain flexible-joint robot arm to produce satisfactory tracking results. The improved fuzzy PI controller not only can control (stable and unstable) conventional linear systems, performing as well as the conventional PI controller, but also is capable of controlling many nonlinear systems such as the flexible-joint robot arm under investigation which contains uncertainties within 10% tolerance of all nominal system-parameter values. In this improved fuzzy PI controller, we used only three simple membership functions plus six simple fuzzy logic control rules. In this paper, we describe the design principle of this controller and demonstrate its tracking performance in handling nonlinearity, flexibility, and uncertainty within the flexible-joint robot arm system.
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In a university, a professor is expected to play a dual role: as teacher and as researcher.
No abstract is provided for this article.
No abstract is provided for this article.
This paper studies two two-component shallow water wave models. From the dynamical systems approach and using the singular traveling wave theory developed by Li and Chen [2007], all possible bounded solutions (solitary wave solutions, pseudo-peakons, periodic peakons, as well as smooth periodic wave solutions) are obtained under different parameter conditions. More than six explicit exact parametric representations are derived. More interestingly, it was found that, for the two-component Camassa–Holm equations with constant vorticity, its [Formula: see text]-traveling wave system has a pseudo-peakon wave solution. In addition, its [Formula: see text]-traveling wave system has four families of uncountably infinitely many solitary wave solutions. The new results complete a recent study of Dutykh and Ionescu-Kruse [2019].
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> 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 synchronization, 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. </para>
