Practical preset time fault-tolerant control of uncertain Euler-Lagrange systems with input saturation and guaranteed performance

The practical preset time fault-tolerant control (FTC) problem is explored in this article for uncertain Euler-Lagrange systems with input saturation and guaranteed performance. To cope with the uncertainty of the Euler-Lagrange systems, the adaptive neural network (NN) is exploited to approximate the unknown continuous function. Most existing results that consider input saturation and actuator faults simultaneously need to design compensation strategies separately, which increases the complexity of control algorithms. To overcome the above obstacle, the Nussbaum gain technique is used to deal with the effects of input saturation and actuator faults in this article. Besides, with the help of error transformation technology and speed function, the proposed control algorithm can ensure that the tracking error converges within the preset time and its overshoot is constrained within the prescribed performance boundaries. Furthermore, the boundedness of all closed-loop system signals is confirmed. Finally, comparative simulation results are depicted to highlight the superiority of the designed control algorithm.