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Huang B.,Fuzhou University | Huang B.,Digital Design Center for Manufacturing of Fujian Province | Gao C.-H.,Digital Design Center for Manufacturing of Fujian Province | Chen L.,Fuzhou University
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | Year: 2010

By considering both fuzzy completion time and fuzzy due date in practice, partner selection in a virtual enterprise under these circumstances was studied. Based on the agreement index to maximize the minimum customer satisfaction, partner selection problem was formulated. For solving the formulated problems, an adaptive genetic algorithm was proposed where fuzzy number processing methods were introduced into the fitness function. The simulation results indicate the feasibility and effectivity of the proposed method. Source


Liang J.,Fuzhou University | Liang J.,Digital Design Center for Manufacturing of Fujian Province | Chen L.,Fuzhou University | Liang P.,China Aerodynamics Research And Development Center
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | Year: 2012

For the general requirement of space robot to have advantages such as long arms and huge load for space on-orbit operation, the flexible problem of mechanical arm should be considered for analyzing space robot's dynamics and control. The coordinated motion control and vibration suppression problems of flexible arm space robot with unknown parameters were discussed. With the law of momentum conservation and assumed mode method, the Lagrange principle was utilized to model the dynamic function of flexible arm space robot. On these bases, mathematical models which were suit for control system design were established by using double time scale decomposition of singular perturbation theory. Aiming at the slow-subsystem, Radial Basis Function (RBF) neural network control algorithm with uncertain parameters was designed to dominate the trajectory tracking of coordinated motion. The research purpose of neural network control algorithm was to improve the control accuracy of whole system based on good on-line self-learning of neural network. For fast-subsystem, hierarchical fuzzy control algorithm was used to control the vibration of flexible link. The research purpose of hierarchical fuzzy control algorithm was to reduce the size of fuzzy rule base, and raises the calculation efficiency of fuzzy controller effectively. Computer simulation results illustrated the effectiveness and feasibility of proposed algorithms. Source


Liang J.,Fuzhou University | Liang J.,Digital Design Center for Manufacturing of Fujian Province | Chen L.,Fuzhou University
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | Year: 2012

Concerned dynamic modeling and control problems are discussed for free-floating flexible arm space robot with uncertain parameters and an uncontrolled base. According to the geometric relationship and law of conversation of momentum, the Lagrange equation of the second kind is utilized to model the dynamic function of the flexible arm space robot incorporating the assumed modes method. By using this model, a neural network L-two-gain robust control scheme with L-two-gain disturbance attenuation is proposed to dominate the base attitude and the joint angle of manipulator to track desired trajectories synchronously in joint space on condition that system parameters are unknown. In order to damp out vibration, conception of virtual force is used to design hybrid desired trajectory which integrate both flexible mode and rigid motion, through transforming the original control scheme and a neural network L-two-gain robust control based on virtual force conception is proposed. The control scheme needs neither linearly parameterize the dynamic equations of the system, nor know any system parameters. Since using the concept of virtual control force, so rigid trajectory track is guaranteed just by inputting one control, and at the same time, active suppression on flexible vibration is made, it's more suitable in practical using for space robot system. Theoretical analysis and simulation results verify the feasibility of the proposed control schemes. ©2012 Journal of Mechanical Engineering. Source


Huang B.,Fuzhou University | Huang B.,Digital Design Center for Manufacturing of Fujian Province | Gao C.,Fuzhou University | Gao C.,Digital Design Center for Manufacturing of Fujian Province | Chen L.,Fuzhou University
2010 International Conference on Computing, Control and Industrial Engineering, CCIE 2010 | Year: 2010

During the partner selection process in a virtual enterprise, the information about the candidates and their performances are incomplete and uncertain. In this paper, vague sets theory is introduced to give comprehensive consideration to truth membership, false membership and uncertainty membership degree of the candidates to satisfy the decision-maker. On the basis of the agreement index of satisfaction degree, the formulated partner selection problems are interpreted so as to maximize the average agreement index. To solve the problem, genetic algorithm is proposed. Finally, the simulation of a case demonstrates that the method is effective. © 2010 IEEE. Source


Huang B.,Fuzhou University | Huang B.,Digital Design Center for Manufacturing of Fujian Province | Gao C.,Fuzhou University | Gao C.,Digital Design Center for Manufacturing of Fujian Province | Chen L.,Fuzhou University
Expert Systems with Applications | Year: 2011

Partner selection is a major issue in the formation of a virtual enterprise. In practice, in the partner selection process, the information about the candidates and their performances are incomplete and uncertain. Vague sets theory is one of the methods used to deal with uncertain information. In this paper, a new method based on vague sets is proposed to deal with the partner selection problem in the formation of a virtual enterprise while the factors of satisfaction degree, due date, cost and the precedence of tasks are taken into account. On the basis of the agreement index of satisfaction degree, the formulated partner selection problems are interpreted so as to maximize the minimum agreement index. To solve the problem, an improved particle swarm optimization (PSO) algorithm is proposed. Finally, the simulation of a numerical example demonstrates that the method is effective. © 2011 Elsevier Ltd. All rights reserved. Source

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