Robust Bipartite Consensus Tracking for Multi-Agent Systems under Acuator Faults
Chenglin Han, Mengji Shi, Rui Li, Jiaqi Lu, Zhiqiang Li, Kaiyu Qin · 2022 IEEE 5th International Conference on Electronics Technology (ICET) · 2022
This paper focuses on the robust bipartite consensus tracking problem of multi-agent systems under actuator faults. Both uncertainties and multiplicative actuator faults are considered in the system model. First, linearly parameterized neural networks are applied to approximate the uncertainty parts. Then, distributed adaptive update laws are designed for the unknown parameters and the actuator fault factors to guarantee the boundedness of estimation error. An adaptive bipartite consensus tracking control algorithm is proposed, which can solve the robust problem and suppress the uncertainties and actuator faults, simultaneously. Furthermore, numerical simulations are given to illustrate the effectiveness of the theoretical analysis.