Abstract
This paper presents a comparison of three common neural network controllers: model predictive control, NARMA-L2 control and model reference control. We describe each of the controllers and demonstrate their performance on four applications: a continuous stirred tank reactor, a robot arm, a magnetic levitation system and a simple diesel engine model. The strengths and weaknesses of each algorithm are illustrated.
Sign-in/Register to access full text options 
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.
