Event-Triggered Prescribed Settling Time Consensus Compensation Control for a Class of Uncertain Nonlinear Systems With Actuator Failures

For a class of uncertain nonlinear systems with actuator failures, the event-triggered prescribed settling time consensus adaptive compensation control method is proposed. The unknown form of actuator failures may occur in practical applications, resulting in system instability or even control failure. In order to effectively deal with the above problems, a neural network adaptive control method is developed to ensure that the system states rapidly converge in the event of failure and compensate for the failures of actuator. Meanwhile, a nonlinear transformation function is introduced to make sure that the tracking error converges for the predefined interval within a prescribed settling time, which makes that the convergence time can be preset. Furthermore, a finite-time event-triggered compensation control strategy is established by the backstepping technology. Under this strategy, the system not only can rapidly stabilize in finite time but also can effectively save network bandwidth. In addition, the states of the system are globally uniformly bounded. Finally, the theoretical analysis and simulation experiments validate the effectiveness of the proposed method.

Automated summary

This paper proposes a control method for uncertain nonlinear systems with actuator failures. By using neural network adaptive control and nonlinear transformation function, the method achieves rapid convergence of system states and compensation for actuator failures when failures occur. Meanwhile, a finite-time event-triggered compensation control strategy is introduced to achieve rapid system stabilization and save network bandwidth.