Abstract

This article addresses the adaptive iterative learning control consensus problem for a class of unknown nonlinear high-order nonstrict feedback multiagent systems with partially unknown virtual and actual control directions and saturation inputs. Due to the unknown nonlinear dynamics of all follower agents, fuzzy logic systems combined with adaptive way are employed to design control protocol. And the Nussbaum-gain method is utilized to deal with partially unknown virtual and actual control directions in each step of the backstepping design procedure. With backstepping design process constructing adaptive fuzzy iterative learning control scheme for each agent, our proposed new control algorithm ensures that the outputs of all follower agents can accurately track the leader on finite time <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$[ {0,T} ]$</tex-math></inline-formula> . Finally, the performance of our new algorithm is demonstrated 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.