The Experts below are selected from a list of 1031964 Experts worldwide ranked by ideXlab platform
Guanrong Chen - One of the best experts on this subject based on the ideXlab platform.
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a connectivity preserving flocking algorithm for multi agent dynamical systems with bounded Potential Function
Iet Control Theory and Applications, 2012Co-Authors: Guanghui Wen, Zhisheng Duan, Guanrong ChenAbstract:Without assuming that the communication topology can remain its connectivity frequently enough and the Potential Function can provide an infinite force during the evolution of agents, the flocking problem of multi-agent systems with second-order non-linear dynamics is investigated in this study. By combining the ideas of collective Potential Functions and velocity consensus, a connectivity-preserving flocking algorithm with bounded Potential Function is proposed. Using tools from the algebraic graph theory and matrix analysis, it is proved that the designed algorithm can guarantee the group of multiple agents to asymptotically move with the same velocity while preserving the network connectivity if the coupling strength of the velocity consensus term is larger than a threshold value. Furthermore, the flocking algorithm is extended to solve the flocking problem of multi-agent systems with a dynamical virtual leader by adding a navigation feedback term. In this case, each informed agent only has partial velocity information about the leader, yet the present algorithm not only can guarantee the velocity of the whole group to track that of the leader asymptotically, and also can preserve the network connectivity. Finally, some numerical simulations are provided to illustrate the theoretical results.
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a connectivity preserving flocking algorithm for nonlinear multi agent systems with bounded Potential Function
Chinese Control Conference, 2011Co-Authors: Guanghui Wen, Zhisheng Duan, Guanrong ChenAbstract:Without assuming that the communication topology can maintain its connectivity frequently enough during the evolution of agents, the flocking problem of multi-agent systems with second-order nonlinear dynamics is investigated in this paper. By combining the ideas of collective Potential Functions and velocity consensus, a connectivity-preserving flocking algorithm with bounded Potential Function is proposed. Using tools from algebraic graph theory and matrix analysis, it is shown that the present algorithm can enable the group of multiple agents to move with the same velocity while preserving the connectivity of the whole network if the the algebraic connectivity of the initial network is larger than a threshold value. Furthermore, the flocking algorithm is used to solve the flocking problem of multi-agent systems with a virtual leader by adding a navigation feedback term. In this case, each informed agent only has partial velocity information about the leader, yet the present algorithm not only can guarantee the velocity of the whole group to track that of the leader asymptotically, and also can preserve the connectivity of the network. Finally, simulation results are provided to valid the effectiveness of the theoretical results.
Guanghui Wen - One of the best experts on this subject based on the ideXlab platform.
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a connectivity preserving flocking algorithm for multi agent dynamical systems with bounded Potential Function
Iet Control Theory and Applications, 2012Co-Authors: Guanghui Wen, Zhisheng Duan, Guanrong ChenAbstract:Without assuming that the communication topology can remain its connectivity frequently enough and the Potential Function can provide an infinite force during the evolution of agents, the flocking problem of multi-agent systems with second-order non-linear dynamics is investigated in this study. By combining the ideas of collective Potential Functions and velocity consensus, a connectivity-preserving flocking algorithm with bounded Potential Function is proposed. Using tools from the algebraic graph theory and matrix analysis, it is proved that the designed algorithm can guarantee the group of multiple agents to asymptotically move with the same velocity while preserving the network connectivity if the coupling strength of the velocity consensus term is larger than a threshold value. Furthermore, the flocking algorithm is extended to solve the flocking problem of multi-agent systems with a dynamical virtual leader by adding a navigation feedback term. In this case, each informed agent only has partial velocity information about the leader, yet the present algorithm not only can guarantee the velocity of the whole group to track that of the leader asymptotically, and also can preserve the network connectivity. Finally, some numerical simulations are provided to illustrate the theoretical results.
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a connectivity preserving flocking algorithm for nonlinear multi agent systems with bounded Potential Function
Chinese Control Conference, 2011Co-Authors: Guanghui Wen, Zhisheng Duan, Guanrong ChenAbstract:Without assuming that the communication topology can maintain its connectivity frequently enough during the evolution of agents, the flocking problem of multi-agent systems with second-order nonlinear dynamics is investigated in this paper. By combining the ideas of collective Potential Functions and velocity consensus, a connectivity-preserving flocking algorithm with bounded Potential Function is proposed. Using tools from algebraic graph theory and matrix analysis, it is shown that the present algorithm can enable the group of multiple agents to move with the same velocity while preserving the connectivity of the whole network if the the algebraic connectivity of the initial network is larger than a threshold value. Furthermore, the flocking algorithm is used to solve the flocking problem of multi-agent systems with a virtual leader by adding a navigation feedback term. In this case, each informed agent only has partial velocity information about the leader, yet the present algorithm not only can guarantee the velocity of the whole group to track that of the leader asymptotically, and also can preserve the connectivity of the network. Finally, simulation results are provided to valid the effectiveness of the theoretical results.
Bo Yuan - One of the best experts on this subject based on the ideXlab platform.
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Potential Function in a continuous dissipative chaotic system decomposition scheme and role of strange attractor
International Journal of Bifurcation and Chaos, 2014Co-Authors: Qijun Tan, Ruoshi Yuan, Bo YuanAbstract:We demonstrate, first in literature, that Potential Functions can be constructed in a continuous dissipative chaotic system and can be used to reveal its dynamical properties. To attain this aim, a Lorenz-like system is proposed and rigorously proved chaotic for exemplified analysis. We explicitly construct a Potential Function monotonically decreasing along the system's dynamics, revealing the structure of the chaotic strange attractor. The Potential Function is not unique for a deterministic system. We also decompose the dynamical system corresponding to a curl-free structure and a divergence-free structure, explaining for the different origins of chaotic attractor and strange attractor. Consequently, reasons for the existence of both chaotic nonstrange attractors and nonchaotic strange attractors are discussed within current decomposition framework.
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Potential Function in a continuous dissipative chaotic system decomposition scheme and role of strange attractor
arXiv: Chaotic Dynamics, 2012Co-Authors: Qijun Tan, Ruoshi Yuan, Bo YuanAbstract:In this paper, we demonstrate, first in literature known to us, that Potential Functions can be constructed in continuous dissipative chaotic systems and can be used to reveal their dynamical properties. To attain this aim, a Lorenz-like system is proposed and rigorously proved chaotic for exemplified analysis. We explicitly construct a Potential Function monotonically decreasing along the system's dynamics, revealing the structure of the chaotic strange attractor. The Potential Function can have different forms of construction. We also decompose the dynamical system to explain for the different origins of chaotic attractor and strange attractor. Consequently, reasons for the existence of both chaotic nonstrange attractors and nonchaotic strange attractors are clearly discussed within current decomposition framework.
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constructive proof of global lyapunov Function as Potential Function
arXiv: Chaotic Dynamics, 2010Co-Authors: Ruoshi Yuan, Bo YuanAbstract:We provide a constructive proof on the equivalence of two fundamental concepts: the global Lyapunov Function in engineering and the Potential Function in physics, establishing a bridge between these distinct fields. This result suggests new approaches on the significant unsolved problem namely to construct Lyapunov Functions for general nonlinear systems through the analogy with existing methods on Potential Functions. In addition, we show another connection that the Lyapunov equation is a reduced form of the generalized Einstein relation for linear systems.
Shengxi Zhou - One of the best experts on this subject based on the ideXlab platform.
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approximate solutions and their stability of a broadband piezoelectric energy harvester with a tunable Potential Function
Communications in Nonlinear Science and Numerical Simulation, 2020Co-Authors: Feng Qian, Shengxi ZhouAbstract:Abstract A broadband piezoelectric energy harvester (PEH) with a mechanically tunable Potential Function is modeled and analytically analyzed. The harvester consisting of a beam and a pre-compression spring at one end can be tuned to both monostable and bistable configurations. The axial motion of the beam resulting from the transverse vibration and spring load induces two coupled higher-order terms of displacement, velocity and acceleration into the governing equations. This significantly complicates the theoretical analysis, especially the stability analysis of solutions. Harmonic balance method is employed to investigate the dynamic characteristics of the nonlinear energy harvester. An effective approach is developed to solve the entries of the Jacobian matrix for determining the stability of analytical solutions. This approach offers a criterion for solution stability analysis of congeneric nonlinear systems with coupled higher-order terms. The energy harvesting performance and the nonlinear dynamic characteristics of the proposed PEH are explored for various base excitation levels, electrical resistive loads and pre-deformations of the spring. The approximate analytical solutions are validated by numerical simulations. Results demonstrate that the energy harvesting performance of the proposed PEH could be effectively tuned by the pre-deformation of the spring. The proposed PEH could harvest vibration energy in a wide frequency range of 0–91 Hz at the excitation level of 0.5 g.
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stochastic resonance energy harvesting for a rotating shaft subject to random and periodic vibrations influence of Potential Function asymmetry and frequency sweep
Smart Materials and Structures, 2017Co-Authors: Hongjip Kim, Weiche Tai, Shengxi Zhou, Lei ZuoAbstract:Stochastic resonance is referred to as a physical phenomenon that is manifest in nonlinear systems whereby a weak periodic signal can be significantly amplified with the aid of inherent noise or vice versa. In this paper, stochastic resonance is considered to harvest energy from two typical vibrations in rotating shafts: random whirl vibration and periodic stick-slip vibration. Stick-slip vibrations impose a constant offset in centrifugal force and distort the Potential Function of the harvester, leading to Potential Function asymmetry. A numerical analysis based on a finite element method was conducted to investigate stochastic resonance with Potential Function asymmetry. Simulation results revealed that a harvester with symmetric Potential Function generates seven times higher power than that with asymmetric Potential Function. Furthermore, a frequency-sweep analysis also showed that stochastic resonance has hysteretic behavior, resulting in frequency difference between up-sweep and down-sweep excitations. An electromagnetic energy harvesting system was constructed to experimentally verify the numerical analysis. In contrast to traditional stochastic resonance harvesters, the proposed harvester uses magnetic force to compensate the offset in the centrifugal force. System identification was performed to obtain the parameters needed in the numerical analysis. With the identified parameters, the numerical simulations showed good agreement with the experiment results with around 10% error, which verified the effect of Potential Function asymmetry and frequency sweep excitation condition on stochastic resonance. Finally, attributed to compensating the centrifugal force offset, the proposed harvester generated nearly three times more open-circuit output voltage than its traditional counterpart.
Haibin Duan - One of the best experts on this subject based on the ideXlab platform.
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target detection approach for uavs via improved pigeon inspired optimization and edge Potential Function
Aerospace Science and Technology, 2014Co-Authors: Haibin DuanAbstract:Abstract In this paper, the hybrid model of Edge Potential Function (EPF) and Simulated Annealing Pigeon-inspired Optimization (SAPIO) algorithm is proposed to accomplish the target detection task for Unmanned Aerial Vehicles (UAVs) at low altitude. EPF can be calculated from the edge map of the original image and provide a kind of attractive pattern for the given target, which is conventionally exploited by the optimization algorithms. Pigeon-inspired Optimization (PIO) is a novel bio-inspired computation algorithm, which was inspired from the homing characteristics of pigeons. In this paper, the simulated annealing mechanism is adopted in our SAPIO algorithm for maximizing the value of EPF. A series of comparative experiments with standard Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colony Optimization (ABC) and PIO algorithms demonstrate the robustness and effectiveness of our SAPIO algorithm. Meanwhile, the proposed approach can guarantee accurate target matching.
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artificial bee colony abc optimized edge Potential Function epf approach to target recognition for low altitude aircraft
Pattern Recognition Letters, 2010Co-Authors: Chunfan Xu, Haibin DuanAbstract:This paper describes a novel shape-matching approach to visual target recognition for aircraft at low altitude. An artificial bee colony (ABC) algorithm with edge Potential Function (EPF) is proposed to accomplish the target recognition task for aircraft. EPF is adopted to provide a type of attractive pattern for a matching contour, which can be exploited by ABC algorithm conveniently. In this way, the best match can be obtained when the sketch image translates, reorients and scales itself to maximize the Potential value. In addition, the convergence proof and computational complexity for the ABC algorithm are also given in detail. Series of experimental results demonstrate the feasibility and effectiveness of our proposed approach over the traditional genetic algorithm (GA). The proposed method can also be applied to solve the target recognition problems in mobile robots, industry production lines, and transportations.
