This paper investigates distributed leader-following swarm of heterogeneous multi-agent systems. Comparing with the existing works on leader-following swarm of homogeneous multi-agent systems, this paper is much more ...
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This paper investigates distributed leader-following swarm of heterogeneous multi-agent systems. Comparing with the existing works on leader-following swarm of homogeneous multi-agent systems, this paper is much more approaching the practical situation because the agents have different dynamics. We show that the heterogeneous followers will gather with a certain error lever under some assumptions and conditions. The stability properties have been proven by theoretical analysis and verified via numerical simulation. The stability of the heterogeneous multi-agent systems has been achieved based on matrix theory and the Lyapunov stability theorem. Numerical simulation is given to demonstrate the effectiveness of the theoretical result.
This paper investigates distributed leader-following swarm stability of heterogeneous multi-agent systems with periodically intermittent control. We assume that the agents in the network are nonidentical and the coupl...
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ISBN:
(纸本)9789881563835
This paper investigates distributed leader-following swarm stability of heterogeneous multi-agent systems with periodically intermittent control. We assume that the agents in the network are nonidentical and the coupling matrix is balanced. Each heterogeneous follower is assumed to obtain some information from the leader and the neighbors only on a series of periodically time intervals. We show that the system will be exponentially stable. The stability properties are proved via theoretical analysis and verified via numerical simulations. The stability of the heterogeneous multi-agent systems is proved based on matrix theory and the Lyapunov stability theorem. A numerical example is shown to demonstrate the effectiveness of the theoretical result.
This paper is concerned with the modeling and the control of networked control systems(NCSs) with stochastic packet *** order to facilitate the technical description,network-induced time delay is assumed to be *** clo...
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ISBN:
(纸本)9781479900305
This paper is concerned with the modeling and the control of networked control systems(NCSs) with stochastic packet *** order to facilitate the technical description,network-induced time delay is assumed to be *** closed-loop NCS with stochastic packet dropout is modeled as a continuous-time system with time-varying delays and stochastic parameters. By utilizing the Lyapunov-Krasovskii functional method,the integral inequality lemma and the Gronwall-Bellman lemma,a less conservative criterion for exponential mean-square stability of NCS with stochastic packet dropout is presented in the form of nonlinear matrix ***,the state feedback gain matrix is provided based on solving a linear matrix inequality (LMI).Moreover,the state feedback gain matrix is obtained by solving a linear matrix inequality(LMI).Based on the solvability of this LMI,the allowable upper bound of continuous packet dropouts is determined,from which the maximum allowable time interval(MATI) can also be ***,a numerical example is given to demonstrate the effectiveness of our results.
This paper presents an investigation on the dynamics of a supply chain system under stock-dependent demand. Considering the feature of piecewise linearity, a switched linear model composed of three subsystems is devel...
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This paper presents an investigation on the dynamics of a supply chain system under stock-dependent demand. Considering the feature of piecewise linearity, a switched linear model composed of three subsystems is developed. Based on the switched model, some analytical stability results are derived. Simulation experiments are designed to verify the stability results and observe nonlinear dynamics. We show that stock-dependent demand not only leads to different stability results but also makes nonlinear dynamics more complicated. We also reveal that the nonlinear dynamics of the switched model, such as chaotic and periodic fluctuations of inventory and order, are essentially caused by switching frequently among subsystems due to uncertainties of inventory status. The results obtained in this paper help us understand the dynamic complexities of supply chain system and provide guidelines for selecting decision parameters to improve overall performance.
Most existing flocking algorithms assume one single virtual leader and rely on information on both relative positions and relative velocities among neighboring *** this paper,the problem of controlling a flock of mobi...
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Most existing flocking algorithms assume one single virtual leader and rely on information on both relative positions and relative velocities among neighboring *** this paper,the problem of controlling a flock of mobile autonomous agents to follow multiple virtual leaders is investigated by using only position information in the sense that agents with the same virtual leader asymptotically attain the same velocity and track the corresponding virtual leader based on only position measurements.A flocking algorithm is proposed under which every agent asymptotically attains its desired velocity,collision between agents can be avoided,and the final tight formation minimizes all agents' global potentials.A simulation example is presented to verify and illustrate the theoretical results.
The prediction of landslide displacement is essential for carrying out to improve the disaster warning system and reduce casualties and property losses. This study applies a novel neural network technique, extreme lea...
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The prediction of landslide displacement is essential for carrying out to improve the disaster warning system and reduce casualties and property losses. This study applies a novel neural network technique, extreme learning machine (ELM) with kernel function, to landslide displacement prediction problem. However, the generalization performance of ELM with kernel function depends closely on the kernel types and the kernel parameters. In this paper, we use a convex combination of Gaussian kernel function and polynomial kernel function in ELM, which may use these two types of kernel functions' advantages. In order to avoid blindness and inaccuracy in parameter selection, a novel hybrid optimization algorithm based on the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) is used to optimize the regularization parameter C, the Gaussian kernel parameter γ, the polynomial kernel parameter q and the mixing weight coefficient η. The performance of our model is verified through two case studies in Baishuihe landslide and Yuhuangge landslide.
This paper proposes a new affine registration algorithm for 2D point matching. It is a two-step iterative registration algorithm by soft weight assignment based on bidirectional distance. At each iteration, the affine...
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ISBN:
(纸本)9781479923427
This paper proposes a new affine registration algorithm for 2D point matching. It is a two-step iterative registration algorithm by soft weight assignment based on bidirectional distance. At each iteration, the affine transformation is updated by two optimization steps, in which the model data and the test data are matched from each other respectively. By the optimization of registration at separate steps during each iteration, the proposed algorithm can provide a good estimate of the accurate affine transformation in condition of poor initialization and lack of geometric assumptions on point sets. Some experiments about comparison with the current state-of-the art approaches, demonstrate the robustness and accuracy of our method.
This paper generalizes the concept of the depth-independent interaction matrix, developed for point and line features in our early work, to generalized image features. We derive the conditions under which the depth-in...
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This paper investigates controllability of discrete-time multi-agent systems with multiple leaders on fixed networks. The leaders are particular agents playing a part in external inputs to steer other member agents. T...
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This paper investigates controllability of discrete-time multi-agent systems with multiple leaders on fixed networks. The leaders are particular agents playing a part in external inputs to steer other member agents. The followers can arrive at any predetermined configuration by regulating the behaviors of the leaders. Some sufficient and necessary conditions are proposed for the controllability of discrete-time multi-agent systems with multiple leaders. Moreover, the case with isolated agents is discussed. Numerical examples and simulations are proposed to illustrate the theoretical results we established.
Membrane computing is an emergent branch of natural computing, which is inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order st...
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Membrane computing is an emergent branch of natural computing, which is inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. Tissue P systems are a class of the most investigated computing mod- els in the framework of membrane computing, especially in the aspect of efficiency. To generate an exponential resource in a polynomial time, cell separation is incorporated into such systems, thus obtaining so called tissue P systems with cell separation. In this work, we exploit the computational efficiency of this model and construct a uniform family of such tissue P systems for solving the independent set problem, a well-known NP-complete problem, by which an efficient so- lution can be obtained in polynomial time.
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