Adaptive sliding mode consensus control based on neural network for singular fractional order multi-agent systems

作者：

Highlights：

• By using a special method to construct a new sliding surface so that the sliding mode is the form of normal system.

• In order to ensure the finite time reachability of the sliding surface, an adaptive SMC law is given.

• The adaptive method based on RBFNN is employed to approximate the unknown nonlinear term.

• The consensus of sliding mode controller for SFOMAS with state feedback is studied.

摘要

•By using a special method to construct a new sliding surface so that the sliding mode is the form of normal system.•In order to ensure the finite time reachability of the sliding surface, an adaptive SMC law is given.•The adaptive method based on RBFNN is employed to approximate the unknown nonlinear term.•The consensus of sliding mode controller for SFOMAS with state feedback is studied.

论文关键词：Sliding mode control,Singular fractional order systems,State feedback control,Radial basis function neural network,Linear matrix inequalities

论文评审过程：Received 10 May 2022, Revised 29 June 2022, Accepted 22 July 2022, Available online 2 August 2022, Version of Record 2 August 2022.

论文官网地址：https://doi.org/10.1016/j.amc.2022.127442