期刊名称:Journal of Software Engineering and Applications
印刷版ISSN:1945-3116
电子版ISSN:1945-3124
出版年度:2012
卷号:5
期号:3
页码:168-189
DOI:10.4236/jsea.2012.53024
出版社:Scientific Research Publishing
摘要:This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.
关键词:Adaptive Internal Model Control; Recurrent Neural Network; DC Motor; Parametric Adaptation Algorithm; Levenberg-Marquardt