The observer information is applied to compensate the amount of sensor faults. The attitude is estimated using an array of nonlinear observer information. In, an attitude fault-tolerant control scheme is proposed for the quadcopter in the presence of sensor faults. Few research papers focus on the sensor FTC system in comparison with the actuator FTC system. In terms of FTC for quadcopter UAVs, most current studies emphasize actuator faults. This requires the emergence of FTC systems. This means that the control system needs to be designed to maintain stability, quality, and normal operation in the presence of faults. Fault diagnosis is not the ultimate goal in the control of a quadcopter system, whereas safety and reliability during operation is a key feature. Although a fault diagnosis algorithm is crucial, it is insufficient to guarantee the normal operation of the quadrotor UAVs. The results show that the proposed method can track quickly and smoothly acceleration commands under actuator faults. Although the virtual control law is designed to handle system uncertainties, the fault-weighing dynamic control allocation is suggested to distribute the control signal for each actuator. This control method consists of two parts: nonlinear virtual control strategy and dynamic control allocation. In the latest article, a fault-tolerant control based on command filter backstepping and dynamic control allocation is proposed for drone interceptors with fixed wings and reaction jets in the presence of actuator faults. The suggested strategy can show a good tracking performance under sensor faults and external disturbances. In, a robust sensor fault detection algorithm based on H ∞ performance is proposed for the quadrotor. A sensor fault diagnosis of a quadrotor UAV based on a two-stage Kalman filter algorithm is considered in. The nonlinear identity observer is suggested to detect faults, and the generalized observer scheme is used to isolate the sensor faults. An FDI scheme with various kinds of sensor faults is examined in. In, a fault diagnosis strategy based on the Thau observer and Lipschitz nonlinear model is presented for a quadrotor considering actuator and sensor faults. In, an FDI and estimation method is presented for a quadrotor in the case of a gyroscope and accelerometer fault. Some studies have shown promised results of an actuator fault diagnosis, but only few works focus on sensor diagnosis for quadrotor UAVs. In, a fault detection and isolation (FDI) based on a neural network in the case of an actuator fault is investigated. Based on the fault estimation information, a nonlinear adaptive controller is suggested to guarantee the stability of the quadrotor system. In, the magnitude of actuator fault is estimated through a parameter estimation scheme. This work is validated through experiment with a quadrotor helicopter testbed. A two-stage Kalman filter algorithm is applied to estimate loss of control effectiveness in each actuator. The online fault parameter is estimated by dual Unscented Kalman filter (UKF). The fault detection and FD is proposed for a realistic non-linear UAV model. The results showed that a fault estimation algorithm can estimate the magnitude of a fault under model uncertainties. In, a robust fault diagnosis based on the Thau observer is presented for the quadcopter in the presence of an actuator fault. Many research studies on fault diagnosis (FD) have been proposed for the quadcopter system. Accordingly, sensor fault diagnosis and fault tolerant control is examined. In this article, the AFTC scheme is investigated for the quadcopter system in the case of sensor fault occurrence. The AFTC scheme can provide better performance in the case of large faults. However, the active FTC (AFTC) scheme has been utilized for fault diagnosis and a fault accommodation approach to tolerate the faults. The passive FTC (PFTC) scheme is designed as a robust controller to reduce fault effects. Normally, FTC techniques are categorized into two groups: active and passive schemes. To overcome this problem, a fault-tolerant control (FTC) technique should be used. In case of actuator or sensor fault occurrence, these controllers cannot maintain normal operation for quadcopters. However, these methods did not consider faults in the quadcopter system. Many control system strategies have been suggested for quadcopters to track desired performance such as adaptive control, fuzzy logic control, gain scheduling, sliding mode control, proportional-integral-derivative control (PID), and artificial intelligence method. To avoid quadcopter UAVs’ crashing during tracking, desired trajectory, and reliable attitude and position control systems are becoming more and more important.
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