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Aiming at the feasibility of intelligent adaptive control for a machining process, a new network architecture, called a hybrid recurrent neural network (HRNN) is first presented based on the diagonal recurrent neural network (DRNN). Considering the uncertain information in the machining process, a generalized entropy square error (GESE) criterion is then proposed. The learning algorithm of the HRNN...
With the aim of validating the feasibility of applying a maximum-entropy-based adaptive control program to the constant force control of a machining process, the maximum-entropy criterion is first introduced. The control flow of the machining process and the mathematic model of the machine tool for experiment are then explained. Finally, both simulation and experiment results are studied to compare...
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