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This paper discusses the off-line identification of friction encountered in the cart motion of an inverted pendulum system. A LuGre model is chosen as the parametric model to represent this phenomenon. We propose an identification technique based on a differential evolution algorithm. The proposed identification technique distinguishes itself from the previous works by optimizing both of the static...
The parameter establishment of differential evolution algorithm (DE) is generally determined by the experience selection method, whose shortcomings include the massive operational parameters, the difficulty in obtaining the best parameter combination, and further obstacle to improve the optimization ability of the algorithm to a great extent. The article introduces the uniform design method of differential...
An important application field of swarm intelligence algorithms is fuzzy rule acquisition. However, their limitations are showed in two aspects. On one hand, it takes a long process to create fuzzy rules during the iterations; on the other, the swarm intelligence algorithms obtain local optimal solution at times. To overcome these disadvantages, a dynamic hybrid swarm intelligence approach is proposed...
Differential Evolution algorithm with Control Parameter Adaptation and Strategy Adaptation(DE-CPASA) is here introduced to solve the problem of parameter estimation. In DE-CPASA, differential evolution operator is used to search the optimization results of problems, and Gaussian distribution is employed to implement the adaptive control parameters. The strategy adaptation is achieved by the evaluation...
In this work, Differential Evolution Algorithm (DEA) is implemented on an embedded systems based on FPGA for the training of multi-layer perceptron (MLP). The classification performance of the MLP trained by DEA on FPGA has been analyzed by using a non-linear database. The MLP performance on FPGA has been compared with that on MATLAB in terms of computational performance and test accuracy. It is proved...
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