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The paper introduces the principle of traditional PID algorithm, analyzes its advantages and disadvantages, and proposes a new control scheme — variable structure fuzzy neural network for such a nonlinear and complex system of automatic Gauge control (AGC). Variable structure fuzzy neural network combines the advantages of neural network and fuzzy control, and also adds a genetic algorithm to optimize...
For academic scientists, it is not satisfy to meet their researches requirements only finding out the basic scientific research activities recent years. The future of research in this field, evolution of the hot spot and the research front of relevant fields has the same Ref. value for current field researching. To solve these problems, we use inspiration discovery method by mining and clustering...
Aiming at the insufficiency of genetic algorithm optimize function parameter, the paper designs the controller based on the clonal algorithm to control the AGC system, the clonal algorithm combines the Gauss variation and the Cauchy variation. The emulation result displays that the means be true of the AGC system and be able to procure better controllability.
The partitioning or clustering method is an important research branch in data mining area, and it partitions the dataset into an arbitrary number k of clusters according to the correlation attribute of all elements of the dataset. Most datasets have the original clusters number, which is estimated with cluster validity index. But most current cluster validity index methods give the error estimation...
A self-tuning PID controller based on adaptive genetic algorithm (AGA) and neural networks is presented. AGA optimizes not only the initial weights of the BP neural networks (BPNN) which optimizes parameters of PID, but also the optimum values of the following radial basis function neural networks (RBFNN) parameters: centers, variance and weights of the output layer. RBFNN identifies the Jacobian...
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