Neural adaptive predefined-time formation tracking control of multiple Euler-Lagrange systems with switching topologies based on hierarchical mechanism☆

作者：Zhao, Xiao-Wen^*; Deng, Dong-Dong; Ge, Ming-Feng; Liu, Zhi-Wei

来源：Chaos Solitons & Fractals, 2024, 178: 114375.

DOI：10.1016/j.chaos.2023.114375

• Predefined-time time-varying formation
• tracking control (PTTVFTC)
• Multiple Euler-Lagrange systems (ELSs)
• Switching topologies
• Neural adaptive fault-tolerant control
• Hierarchical control mechanism (HCM)

This paper investigates the event-triggered neural adaptive predefined-time time-varying formation tracking control (PTTVFTC) problem for multiple Euler-Lagrange systems (ELSs) with actuator failures and saturation under switching communication topologies. The hierarchical control mechanism (HCM) is employed to overcome the difficulties posed by switching communication topologies to design the control algorithms. Specifically, a new estimator is first developed in the estimator layer for each follower, which can estimate the leader's position information within a predefined time. Then, based on the designed estimator, a fault -tolerant and anti-saturation controller is proposed in the local control layer for each follower, which enables each follower to achieve PTTVFTC. To reduce the communication frequency, an event-triggered mechanism (ETM) that does not have Zeno behavior determines the controller's update. In addition, the settling time for formation tracking can be arbitrarily specified as desired. Finally, the effectiveness of the developed control strategy is verified by a simulation experiment.

• 单位
  华中科技大学; 合肥工业大学; 中国地质大学（北京）