Model-free adaptive iterative learning bipartite containment control for multi-agent systems

HIGHLIGHTS

  • who: Shangyu Sang and colleagues from the School of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao, China have published the paper: Model-Free Adaptive Iterative Learning Bipartite Containment Control for Multi-Agent Systems, in the Journal: Sensors 2022, 22, 7115. of /2022/
  • what: By the dynamic linearization method the authors propose a novel model-free adaptive iterative learning control (MFAILC) to solve the bipartite containment problem of MASs. Inspired by normalized least mean squares, the authors design the objective function J (u03c6u0302i (N, hu0304))=|u2206yi (N + 1, hu0304 - 1) - u03c6u0302i (N, hu0304 . . .

     

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