Abstract
This paper presents an attractive artificial neural network (ANN) architecture with novel type of activation functions based on orthonormal function for modelling and control of non-linear processes. Theoretical methodology and design of algorithm for modelling and self-tuning control of uncertain non-linear complex processes is proposed. Several types of orthonormal functions (Fourier, Legendre, Laguerre and Chebychev) for non-linear process modelling and control are analysed and compared. Simulation results are provided to illustrate high performance of artificial neural networks with the orthonormal activation functions (OAFN) in practical problem solutions . The obtained results are compared and potential shortcomings of the proposed methods for real time industry control are discussed and analysed.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
