Vibration-assisted swing cutting (VASC) is a new precision machining technology. VASC not only inherits the characteristics of EVC intermittent cutting but also alleviates the problem of EVC residual height. However, ...
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Vibration-assisted swing cutting (VASC) is a new precision machining technology. VASC not only inherits the characteristics of EVC intermittent cutting but also alleviates the problem of EVC residual height. However, system identification is key if you want to achieve precise control. In order to solve this problem, a new improveddifferentialevolutionary (IDE) algorithm is proposed to identify and optimize the Hammerstein-Wiener model parameter in VASC system. IDE algorithm is applied to transform the identification problem of the model into the optimization problem in the parameter space, and the optimal solution of the parameter of the model in the parameter space is obtained. Meanwhile, the IDE algorithm and the conventional five differentialevolutionaryalgorithms perform performance comparison tests on six different test functions. The test results show that the IDE algorithm is strengthening the global search capability, accelerate the convergence rate to the global optimal solution, and indicate that the IDE algorithm can be effectively applied to the parameter optimization of Hammerstein-winner model. Based on the input and output data collected from the experiment, the accuracy of the identification model can be up to 98%, which prove the superiority of the proposed IDE algorithm for system identification.
With the rapid development of communication technology, more and more devices tend to be intelligent. Intelligent devices with computing functions can provide computing services to reduce total task completion time in...
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ISBN:
(纸本)9781728172361
With the rapid development of communication technology, more and more devices tend to be intelligent. Intelligent devices with computing functions can provide computing services to reduce total task completion time in fog computing networks. This paper aims at minimizing the total task completion time to study multi-user multi-node multi-task offloading problem. Firstly, the task offloading process of task node and fog node is modeled. Then, the system function of the total task completion time is constructed and an optimization problem with constraints is generated. The problem is NP-hard and difficult to be solved by traditional methods. Finally, the improveddifferential evolution (IDE) algorithm is used to solve the task offloading problem. Simulation results show that it has better performance and can significantly shorten the total task completion time compared with other algorithms.
Due to its simple construction, the linear induction motor (LIM) provides a linear driving force without any intermediate motion translation system. LIMs are widely used in various industrial applications, including m...
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Due to its simple construction, the linear induction motor (LIM) provides a linear driving force without any intermediate motion translation system. LIMs are widely used in various industrial applications, including maglev rail transit and the national defense industry. However, LIMs are affected by the end effect and suffer from problems such as low efficiencies and low power factors. To make improvements, in this paper, an ensemble multi-objective optimal design method for a short primary double-sided linear induction motor (SP-DLIM) is proposed. First, a simplified Quasi-3D equivalent circuit model (ECM) for an SP-DLIM applicable to the model in this paper is derived. The 3-D transient finite element method and an experimental prototype are utilised to prove that the derived ECM is accurate enough to solve the SP-DLIM optimisation problem. Second, an ensemble multi-objective optimal design method of SP-DLIM is presented, with proposed design constraints and four different optimisation problems. Then, an improveddifferentialevolutionary (IDE) algorithm is proposed to optimise the efficiency, power factor, and tooth weight of the motor. The three-dimensional time-stepping finite element method is utilised to verify the validity of the optimisation method. Further, a comparison of the results suggests that the IDE yields the best performance to those of other advanced heuristic algorithms.
To solve the partner selection problem in agile manufacturing, the paper comes up with a improved differential evolutionary algorithm for the problem, which compares with the classic differential Evolution algorithm, ...
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ISBN:
(纸本)9781467344975
To solve the partner selection problem in agile manufacturing, the paper comes up with a improved differential evolutionary algorithm for the problem, which compares with the classic differential Evolution algorithm, The algorithm has the advantages of simple structure, fast convergence rate and good robustness. Experiment indicates that the Multi-child differentialevolutionaryalgorithm to solve the partner selection problem is excellent in quality, stability and convergence rate.
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