Adaptive finite time fault tolerant control for the quadrotor unmanned aerial vehicles based on time‐triggered strategy

Abstract

This article investigates the adaptive finite time tracking control problem for quadrotor unmanned aerial vehicles (QUAV) subject to actuator failure with event-triggered control strategy. It is assumed that the models of actuator failure are actuator blockage and saturation faults. The finite time performance function and adaptive backstepping method are combined to design the controller to compensate the influence of actuator failure, so as to ensure that the tracking error converges to the preset neighborhood near the origin in finite time. In addition, a new event-triggered strategy is introduced to save communication resources and avoid the Zeno-behavior, which defines the variable threshold as a function combining with tracking error and positive constants.The variable threshold not only effectively reduces triggering times, but also makes the design of the controller more flexible. It is proved that the closed-loop system is stability. Finally, the effectiveness of this method is verified by simulation.

Adaptive finite-time fault-tolerant control for Robot trajectory tracking systems under a novel smooth event-triggered mechanism

“…To describe the dynamic models of the quadrotor UAV, denote O e x e y e z e as the earth-fixed frame and O b x b y b z b as the body-fixed frame. The dynamic models of a quadrotor UAV can be expressed as 6,23,34…”

“…Combining with discrete-time ESO and event-triggered mechanism, He et al 31 and Shao et al 32 proposed model-free controllers with external disturbances. In pursuit of faster convergence, adaptive finite-time event-triggered control 33,34 has been presented. To address the difficulty of establishing accurate dynamic models, Lin et al 35 proposed an event-triggered reinforcement learning model-free control strategy for stabilizing UAVs with actuator saturation.…”

Geometric prescribed‐time control of quadrotors with adaptive extended state observers

“…Quadrotor has got considerable attention for its advantages in structural simplicity, long endurance, operational convenience, and agility. Many control methods have been given rise to address the stabilization and tracking problems of quadrotors like model predictive control, 1,2 backstepping, [3][4][5][6][7][8][9][10] finite-time control, [11][12][13] sliding mode control 14,15 and so forth.…”

“…The event-triggered controller for quadrotors with actuator faults was used to address the finite-time tracking control problem. 12 It is challenging to achieve the prescribed performance within a finite time T for the above research if there is uncertainty or unknown in the initial condition. Then, fixed-time control approach 8,10,14 was proposed with bounded convergence time that does not take into account the initial state.…”

Position and Attitude Control Based on Single Neuron PID With Gravity Compensation for Quad Rotor UAV

“…Because the quad rotor UAV has the characteristics of strong coupling, nonlinearity and under actuation, the control method has been one of main research directions. At present, many control methods, such as PID control (Miranda-Colorado and Aguilar 2020; Rosales et al 2018), sliding mode control (Mofid and Mobayen 2018;Oba et al 2018;Zhang et al 2021), intelligent control (Guan et al 2021), backstepping control (Zhou et al 2018), L1 Adaptive control (Souanef 2023), fault tolerant control (Di et al 2023), and robust control (Weng et al 2022;Yang 2021) have been applied to the control of quad rotor UAV. Though the traditional PID controller is easily used to implement the control of the quad rotor UAV, the fixed PID parameters cannot adapt to the changes of external conditions and control object parameters, which makes it difficult to achieve the desired control effect.…”