Abstract
A framework for robust neural network-based control of nonlinear servomechanisms is proposed and presented. This framework utilizes a general controller structure that comprises a nonlinear compensation block and a robust control block. Two different strategies for designing the control laws for these are discussed and it is shown that uniform stability of the overall system even in the presence of modeling mismatches and non-parametric uncertainly is achieved. The effectiveness of this proposed framework is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load.
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.
