Abstract
An adaptive neural network (NN) predictive control algorithm is proposed for a class of uncertain discrete-time nonlinear systems with input-delay. For approximate the nonlinear part of the uncertain discrete-time nonlinear system, the recurrent neural network (RNN) is employed. A version of discrete-time NN weight update rule is given. For compensate the reconstructive error of the RNN and the external disturbances, the robust control term is designed. In order to compensate the time-delay in input channel, a predictive control algorithm is proposed. Then the synchronous tracking objective can be realized. An illustrative example is provided to demonstrate the effectiveness of the proposed control strategy.
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.
