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標題: 類神經網路式最佳參數設計法則
Neural Network Based Optimal Design Method
作者: 吳嘉哲
關鍵字: 共軛梯度法;類神經網路式最佳參數設計法則;直交表
出版社: 機械工程學系

Neural network based optimal design method, a new methods that combines the neural network and the Taguchi techniques for better improvement of engineering design is proposed in this thesis. In this new parameter design method, orthogonal array, which requires partial experiments is executed first. Each row in the orthogonal array along with its relative responses form a set of training pattern to the neural network. Implicit system model that allows precise prediction and easy optimizing is constructed in terms of a multilayer feedforward neural network. With the neural network based system model, optimal parameters to achieve desired output can be obtained through direct inverse or numerical methods such as steepest descent and conjugate gradient.
Computer simulations show that the proposed method can easily find the extreme points of an unknown complex nonlinear problem. In real application, the proposed method is used to tune the optimal PID parameters for precise positioning and circular tracking of a DC brushless linear motor system. Both computer simulation and experimental results illustrate that the proposed algorithm performs much better than the conventional Taguchi approach.
Appears in Collections:機械工程學系所

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