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Dynamical behaviors of fuzzy cellular neural networks with discrete time delays

Annali dell'Universita di Ferrara 2010年第1期56卷 181-194页

作者： Zhang, Qianhong Yang, Lihui Guizhou Key Laboratory of Economics System Simulation Guizhou College of Finance and Economics 550004 Guizhou Guiyang China Basic Science Department Hunan Institute of Technology 421002 Hunan Hengyang China Department of Mathematics Hunan City University 413000 Hunan Yiyang China

This paper is concerned with the dynamical behavior of fuzzy cellular neural networks with discrete time delays. By constructing proper Lyapunov functional, applying inequality technique and the homeomorphism theory, some new sufficient conditions checking the existence, uniqueness of the equilibrium point and its global exponential stability are obtained for fuzzy cellular neural networks. The results of this paper are new and they complement previously known results, Moreover an example is given to show the effectiveness of the obtained results. © 2010 Università degli Studi di Ferrara.

关键词： Equilibrium point Fuzzy cellular neural networks Global exponential stability Homeomorphism theory Lyapunov functional

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Structural optimization of lennard-jones clusters by hybrid social cognitive optimization algorithm

Structural optimization of lennard-jones clusters by hybrid ...

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IEEE International Conference on Cognitive Informatics

作者： Yongjing Chen Zhihua Cui Jianchao Zeng Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Taiyuan Shanxi China

Structural optimization of Lennard-Jones (LJ) clusters is a classical NP problem. There are many local minima locating near the global minimum, and the local optima number is increased exponentially. Social cognitive optimization algorithm (SCOA) is a new swarm intelligent technique by simulating the human society. However, its local search capability is still weak. Therefore, in this paper, a novel local search strategy, Limited memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) is employed to enhance the exploitation capability of SCOA. simulation results show the proposed hybrid algorithm has successfully found the lowest-energy structures of the LJ2-LJ5, LJ7-LJ9 and LJ12 comparing with PSO and the standard SCOA.

关键词： Optimization Clustering algorithms Indexes Particle swarm optimization Humans Electronic mail simulation

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The convergence analysis and parameter selection of Artificial Physics Optimization algorithm

The convergence analysis and parameter selection of Artifici...

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International Conference on Modelling, Identification and Control (ICMIC)

作者： Liping Xie Ying Tan Jianchao Zeng Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Taiyuan Shanxi China

Artificial Physics Optimization (APO) algorithm is a population-based stochastic algorithm based on Physicomimetics framework. The algorithm utilizes an attraction-repulsion mechanism to move individuals toward optimality. The convergence analysis of APO algorithm is made theoretically. By regarding each individual's position on each evolutionary step as a stochastic vector, APO algorithm determined by non-negative real parameter tuple {w, G} is analyzed using discrete-time linear system theory. The convergent condition of APO algorithm and corresponding parameter selection guidelines are derived. The simulation results show that the convergent condition is effective in guiding the parameter selection of APO algorithm and can help to explain why those parameters work well.

关键词： Analytical models

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A hybrid group search optimizer with metropolis rule

A hybrid group search optimizer with metropolis rule

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International Conference on Modelling, Identification and Control (ICMIC)

作者： Juanyan Fang Zhihua Cui Xingjuan Cai Jianchao Zeng Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Taiyuan Shanxi China

Group search optimizer (GSO) is a new novel swarm intelligent technique by simulating animal behavioral ecology. However, as a stochastic optimization algorithm, it is still easily trapped into local optima when dealing with multi-modal optimization problems. Therefore, in this paper, a new variant of GSO is designed by hybriding Metropolis rule to further enhancing the capability escaping from local optima. simulation results show the performance of this new variant is superior to the standard group search optimizer and particle swarm optimization in multi-model problems especially for high-dimensional cases.

关键词： Biological system modeling

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RETRACTED ARTICLE: Crank block steering mechanism optimization for forklift truck based on PSO

RETRACTED ARTICLE: Crank block steering mechanism optimizati...

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作者： Sun, Chaoli Zeng, Jianchao Pan, Jengshyang Tao, Yuanfang Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Taiyuan Shanxi 030024 China Department of Electronic Engineering National Kaohsiung University of Applied Sciences Kaohsiung 807 Taiwan Mechanical and Electronic Engineering College Taiyuan University of Science and Technology Taiyuan Shanxi 030024 China

ISBN: (纸本)9781424463503

Crank block steering mechanism optimization is a nonlinear constrained optimization problem, which is important for forklift truck to get preferable steering performance. Particle swarm optimization (PSO) with feasibility-based rules is a swarm intelligent algorithm proposed to solve constrained optimization problems simply and effectively. Therefore, it is used to optimize crank block steering mechanism of forklift truck, which will try to minimize the maximal error of outer wheel steering angle, maximize the minimal transmission angle and improve the force transmission. Experimental results obtained by PSO with feasibility-based rules are compared with those obtained by enumeration algorithm which is reliable for optimization problems. The comparison results showed that particle swarm optimization with feasibility-based rules can get same optimal results as enumeration algorithm in much less calculation times. © 2010 IEEE.

关键词： Particle swarm optimization (PSO)

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Effects of algorithmic parameters on swarm robotic search

Effects of algorithmic parameters on swarm robotic search

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2010 IEEE International Conference on Information and Automation, ICIA 2010

作者： Tan, Ying Xue, Songdong Zeng, Jianchao Pan, Jengshyang Pan, Tienszu Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology No. 66 Waliu Road Taiyuan Shanxi 030024 China Department of Electronic Engineering National Kaohsiung University of Applied Sciences Kaohsiung 807 Taiwan

ISBN: (纸本)9781424457021

As one of valid modeling and coordinated controlling tools, the particle swarm optimization algorithm can be extended for applying to task of swarm robotic search. To gain an insight into effects of key parameters on distributed swarm search, a series of simulations are conducted. In such control algorithm, main parameters including communication range, detection radius, and swarm size are paid close attentions. Similar to ideal "particles", swarm robots are modeled at an abstract level with the extended particle swarm optimization method. Also, individual robots are designed to be controlled under three-state finite state machine mechanism having SingleSearch, SwarmSearch, and Declaration states. Then, control strategy and algorithm are developed. The statistical results from simulating data indicate the validity of modeling approach. Further, the effects of three parameters on overhead and efficiency of system running come out in compared analysis both of different size swarms and of specific size swarm. ©2010 IEEE.

关键词： Swarm intelligence

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A rapid reentry trajectory planning method for CAV

A rapid reentry trajectory planning method for CAV

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International Symposium on systems and Control in Aerospace and Astronautics (ISSCAA)

作者： Zhiqiang Zhao Zhengdong Hu National University of Defense Technology Changsha China Complex Systems Simulation-II National Key Laboratory of Science and Technology Beijing China

ISBN: (纸本)9781424460434

A rapid reentry trajectory planning method for a common aero vehicle (CAV) subject to all path constraints is developed. The reentry trajectory is divided into initial descent phase and quasi-equilibrium glide phase which possesses a majority of the reentry period. An improved quasi-equilibrium glide condition is utilized to convert reentry corridor constraints to the control variable constraints and get a simple relation between the range-to-go and velocity. Accordingly the longitudinal reference trajectory is computed through the one-parameter search of bank angle model and the corresponding tracking law is designed using linear quadratic regulator theory. To enhance the maneuvering capability, a geometrical control approach considering no-fly zone constraints is applied to the lateral guidance. Finally, the performance of this method is verified by computer simulation.

关键词： Trajectory Aerodynamics Planning Vehicles Heating Earth Mathematical model

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Research on an ARC welding robot controller with open architecture and the swing-welding interpolation algorithm

Research on an ARC welding robot controller with open archit...

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International Conference on Advanced technology of Design and Manufacture, ATDM 2010

作者： Zhang, Kailiang Liang, Zize Li, En Yang, Degang Key Laboratory of Complex System and Intelligent Science Institute of Automation Chinese Academy of Sciences Beijing 100190 China Ningbo and Zhongzi Information Technology Research Co. Ltd. Hangzhou Bay Zone Ningbo 315300 China

ISBN: (纸本)9781849192385

This article introduces an open architecture for arc welding robot controller with self-defined Harting-bus structure. Each sub-board composes the controller and is connected to a bus base-plate through unified electrical interface (Harting-Terminal). Each module is flexible and it can be customized to further promotion of the controller so that non R&D personnel can be able to cut or extend the controller function according to specific engineering requirements. In the swing welding control stage, a track interpolation algorithm that gives priority to analytical method is applied to arc welding robot controller. The algorithm can be applied to the swing welding of straight line, and also to the sinusoidal-swing welding that takes spatial smooth curve as the baseline. Preliminary experimental results show that the arc welding robot controller can realize the motion control of 6 degree-of-freedom with industrial welding operation, and particularly it can achieve good results for sinusoidal-swing welding along with spatial circular arc and quadratic curve.

关键词： Interpolation

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Chaotic synchronization in RCL-shunted Josephson junctions

Chaotic synchronization in RCL-shunted Josephson junctions

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作者： Lu, Pingli Yang, Ying School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China Department of Mechanics and Engineering Science Peking University Beijing 100871 China

ISBN: (纸本)9787894631046

Chaotic synchronization criteria for a class of dynamical networks with each node being RCL-shunted Josephson junction is proposed in this paper. The proposed algorithms, which are established in terms of linear matrix inequalities (LMIs), guarantee the synchronized states to be global asymptotically stable. In addition, an interesting conclusion is reached that the chaotic synchronization in the coupled whole 3N-dimensional networks can be converted into that of 3-dimensional space.

关键词： Linear matrix inequalities

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A Hybrid Vector Artificial Physics Optimization with One-Dimensional Search Method

A Hybrid Vector Artificial Physics Optimization with One-Dim...

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International Conference on Computational Aspects of Social Networks(国际社会网络计算会议 CASoN 2010)

作者： Gangjun Yang Liping Xie Jianchao Zeng Ying Tan Key Laboratory of Contemporary Design and Integrated Manufacturing Technology Ministry of Education Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technolog

The direction of each individual velocity vector is very useful information for search in Artificial Physics Optimization (APO) algorithm. APO's simple way to dealing with the errant individual exceeded the lower or upper bounds constrains changes the direction of its motion vector. A shrinkage coefficient is introduced to ensure that each individual is within the decision space without changing its direction. One-dimensional search method is merged into the vector model of APO (VM-APO) to improve its local search capability. The simulation results confirm that the performance of the hybrid vector APO with one-dimensional search method is effective.

关键词： Physicomimetics Artificial physics optimization Global optimization Virtual force Newton's Second law

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