Abstract
In this article an indirect adaptive control method based on a hybrid system identification environment consisting of an Artificial Neural Network (ANN) and a parameter estimator is introduced which manages variable speed navigation, unmodeled dynamics and faults. While the ANN delivers a one step ahead prediction of output of a nonlinear function representing the unmodeled dynamics/additive faults, the parameter estimation technique provides an evaluation of the parameters of the unknown system which may also vary due to changes in the operating conditions and or multiplicative faults.
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.
