Abstract
This paper presents an attractive artificial neural network architecture with orthonormal type of activation functions (e.g. harmonic, Legendre, Laguerre and Chebychev) for modeling and self-tuning control of nonlinear processes. An algorithm for modeling and self-tuning control of uncertain nonlinear complex processes is proposed. Several types of orthonormal functions for nonlinear process modeling and control are analyzed and compared. Simulation results are provided to illustrate high performance of artificial neural networks with the orthonormal activation functions in practical industrial problems. The obtained results are compared and potential shortcomings of the proposed methods for real time industry control are discussed and analyzed.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: 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.