Application of feedforward and recurrent neural networks for model-based control systems
Marek Krok
Wojciech P.Hunek
Szymon Mielczarek
Filip Buchwald
Adam Kolender
Department of Control Science and Engineering,Opole University of Technology,Opole,Poland
摘要:In this paper,a new study concerning the usage of artificial neural networks in the control application is given.It is shown,that the data gathered during proper operation of a given control plant can be used in the learning process to fully embrace the control pattern.Interestingly,the instances driven by neural networks have the ability to outperform the original analytically driven scenarios.Three different control schemes,namely perfect,linear-quadratic,and generalized predictive controllers were used in the theoretical study.In addition,the nonlinear recurrent neural network-based generalized predictive controller with the radial basis function-originated predictor was obtained to exemplify the main results of the paper regarding the real-world application.
机标关键词:applicationsystemscontrolfeedforwardmodel-basednetworksneuralrecurrent
论文发表日期:2025-02-04
在线出版日期:2025-08-15(本平台首次上网日期,不代表文献的发表时间)
页数:14( 91-104 )
英文信息展开
控制理论与技术(英文版)

控制理论与技术(英文版)

EICSCD
ISSN:2095-6983
年,卷(期):2025,23(1)
所属栏目:RESEARCH ARTICLES