Iterative Learning Consensus of Fractional-Order Multi-Agent Systems Subject to Iteration-Varying Initial State Shifts

• Published in: IEEE access Vol. 7; pp. 173063 - 173075
• Main Author: Wang, Liming
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analytical models; consensus tracking; Convergence; Dynamic models; Fractional-order multi-agent systems; iteration-varying initial state shifts; iterative learning control; Iterative methods; Learning; Multi-agent systems; Multiagent systems; Protocols; Robustness (mathematics); Tracking errors; Tracking problem; Trajectory; Two dimensional analysis; Two dimensional displays; Two dimensional models; two-dimensional analysis approach

This paper investigates the robust consensus tracking problem of fractional-order multiagent systems (FOMASs) subject to the iteration-varying initial state shifts. For the FOMASs including one leader agent and multiple follower agents, the PD α -type ILC protocol with the rectifying action is propo...