Abstract

AbstractIn this paper, by making use of recurrent neural networks (RNNs), a novel event‐based robust optimal controller is designed for a category of continuous‐time (CT) nonlinear nonaffine systems with disturbances. For tackling the optimal‐robust problem transformation and the performance guarantee, a system identifier is developed to reconstruct the system, and an event‐triggered critic‐only strategy is investigated to replace the traditional time‐based actor‐critic structure. The RNN is adopted to reconstruct the nonaffine system as an identifier for obtaining the affine model. It simplifies the system structure and reduces computational burdens. In addition, the stability of the unknown nominal system learned by the RNN is proved. Then, using the obtained system identifier and the adaptive critic learning structure, the proposed event‐triggered robust control with performance guarantee is realized. At last, the effectiveness of the given design method is verified by two simulation examples.

Full Text
Paper version not known

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 call

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.