Title :
Knowledge modeling for classical control theory based on neural network
Author :
Yi, Jun ; Li, Taifu ; Ge, Jike ; Su, Yingying ; Hu, Wenjin
Author_Institution :
Dept. of Electr. & Inf. Eng., Chongqing Univ. of Sci. & Technol., Chongqing, China
Abstract :
The design is mainly directed against neural network has a strong nonlinear mapping ability to be effective in the expression of expertise and know-how to the establishment of empirical knowledge of experts from the input space to the output of the nonlinear mapping space. Classic control theory, such as root locus method and frequency response methods, are also called by experience and knowledge of experts. Therefore, this issue is envisaged that the use of the function of neural networks to solve classical correction control system to solve the problem of controller parameters.
Keywords :
control system synthesis; frequency response; neurocontrollers; nonlinear control systems; root loci; classical correction control system; frequency response method; knowledge modeling; neural network; nonlinear mapping space; root locus method; Artificial neural networks; Computational modeling; Control systems; Control theory; Knowledge engineering; Mathematical model; Training; Classical control theory; Knowledge model; Neural networks; controller parameters;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2011 9th World Congress on
Conference_Location :
Taipei
Print_ISBN :
978-1-61284-698-9
DOI :
10.1109/WCICA.2011.5970719
