Adaptive fault-tolerant tracking control of flying-wing unmanned aerial vehicle with system input saturation and state constraints

2021 ◽  
pp. 014233122110270
Author(s):  
Zhen Li ◽  
Xin Chen ◽  
Mingyang Xie ◽  
Zhenhua Zhao
Keyword(s):  
Reinforcement Learning ◽  
Unmanned Aerial Vehicle ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Input Saturation ◽  
Control Technique ◽  
Attitude Tracking ◽  
Aerial Vehicle ◽  
Fast Dynamic ◽  
Dynamic Subsystem

In this paper, an adaptive fault-tolerant attitude tracking controller based on reinforcement learning is developed for flying-wing unmanned aerial vehicle subjected to actuator faults and saturation. At first, the attitude dynamic model is separated into two dynamic subsystems as slow and fast dynamic subsystems based on the principle of time scale separation. Secondly, backstepping technique is adopted to design the controller. For the purpose of attitude angle constraints, the control technique based on Barrier Lyapunov is used to design controller of slow dynamic subsystem. Considering the optimization of the fast dynamic subsystem, this paper introduces an adaptive reinforcement learning control method in which neural network is used to approximate the long-term performance index and lumped fault dynamic. It is shown that this control algorithm can satisfy the requirements of attitude tracking subjected to the control constraints and the stability of the system is proved from Lyapunov stability theory. The simulation results demonstrate that the developed fault-tolerant scheme is useful and has more smooth control effect compared with fault-tolerant controller based on sliding mode theory.

Tracking Control Design for Quadrotor Unmanned Aerial Vehicle

2017 ◽  
Vol 67 (3) ◽  
pp. 245 ◽  
Author(s):  
Sudhir Nadda ◽  
A. Swarup
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Control Strategy ◽  
Tracking Control ◽  
Control Method ◽  
Sliding Mode ◽  
Backstepping Control ◽  
Control Technique ◽  
Quadrotor Uav ◽  
Attitude Tracking ◽  
Aerial Vehicle

The model of a quadrotor unmanned aerial vehicle (UAV) is nonlinear and dynamically unstable. A flight controller design is proposed on the basis of Lyapunov stability theory which guarantees that all the states remain and reach on the sliding surfaces. The control strategy uses sliding mode with a backstepping control to perform the position and attitude tracking control. This proposed controller is simple and effectively enhance the performance of quadrotor UAV. In order to demonstrate the robustness of the proposed control method, White Gaussian Noise and aerodynamic moment disturbances are taken into account. The performance of the nonlinear control method is evaluated by comparing the performance with developed linear quadratic regulator and existing backstepping control technique and proportional-integral-derivative from the literature. The comparative performance results demonstrate the superiority and effectiveness of the proposed control strategy for the quadrotor UAV.

L1 neural network adaptive fault-tolerant controller for unmanned aerial vehicle attitude control system

2021 ◽  
pp. 095441002098409
Author(s):  
Yan Zhou ◽  
Huiying Liu ◽  
Huijuan Guo ◽  
Jing Li
Keyword(s):  
Neural Network ◽  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Attitude Control ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Attitude Control System ◽  
Attitude Tracking ◽  
Nonlinear Uncertainties ◽  
Aerial Vehicle

In this article, a L1 neural network adaptive fault-tolerant controller is exploited for an unmanned aerial vehicle attitude control system in presence of nonlinear uncertainties, such as system uncertainties, external disturbances, and actuator faults. A nonlinear dynamic inversion controller with sliding mode control law is designed as the outer-loop controller to track the attitude angles quickly and accurately which reduces dependence on model accuracy. A L1 neural network adaptive controller of the inner loop is introduced to compensate the nonlinear uncertainties and have a good attitude tracking. The radial basis function neural network technique is introduced to approximate a lumped nonlinear uncertainty and guarantee the stability and transient performance of the closed-loop system, instead of converting it to a half-time linear system by the parametric linearization method. Simulation results demonstrate the effectiveness of the proposed controller.

scholarly journals Sliding Mode Fault Tolerant Control for Unmanned Aerial Vehicle with Sensor and Actuator Faults

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 643 ◽  
Author(s):  
Juan Tan ◽  
Yonghua Fan ◽  
Pengpeng Yan ◽  
Chun Wang ◽  
Hao Feng
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Health Management ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Control Process ◽  
Fault Tolerant Control ◽  
Accelerometer Sensor ◽  
Actuator Failures ◽  
Aerial Vehicle ◽  
Gyroscope Sensor

The unmanned aerial vehicle (UAV) has been developing rapidly recently, and the safety and the reliability of the UAV are significant to the mission execution and the life of UAV. Sensor and actuator failures of a UAV are one of the most common malfunctions, threating the safety and life of the UAV. Fault-tolerant control technology is an effective method to improve the reliability and safety of UAV, which also contributes to vehicle health management (VHM). This paper deals with the sliding mode fault-tolerant control of the UAV, considering the failures of sensor and actuator. Firstly, a terminal sliding surface is designed to ensure the state of the system on the sliding mode surface throughout the control process based on the simplified coupling dynamic model. Then, the sliding mode control (SMC) method combined with the RBF neural network algorithm is used to design the parameters of the sliding mode controller, and with this, the efficiency of the design process is improved and system chattering is minimized. Finally, the Simulink simulations are carried out using a fault tolerance controller under the conditions where accelerometer sensor, gyroscope sensor or actuator failures is assumed. The results show that the proposed control strategy is quite an effective method for the control of UAVs with accelerometer sensor, gyroscope sensor or actuator failures.

Output feedback observer-based dynamic surface controller for quadrotor UAV using quaternion representation

2016 ◽  
Vol 231 (14) ◽  
pp. 2537-2548 ◽  
Author(s):  
Jingxin Dou ◽  
Xiangxi Kong ◽  
Xiaozhe Chen ◽  
Bangchun Wen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Output Feedback ◽  
Dynamic Surface Control ◽  
Control Technique ◽  
Dynamic Surface ◽  
Attitude Tracking ◽  
Uncertain Disturbances ◽  
Aerial Vehicle ◽  
System Output ◽  
Quaternion Representation

An output feedback observer-based dynamic surface controller is presented for attitude tracking problem of the quadrotor unmanned aerial vehicle, which is subject to measurement noise and external disturbances. The dynamics model of the quadrotor unmanned aerial vehicle is firstly introduced with the quaternion representation. Subsequently, a nonlinear augmented observer is introduced for simultaneously estimating the unavailable states and uncertain disturbances from the measurement of system output. The output feedback controller based on the nonlinear augmented observer is designed with the dynamic surface control technique. The Lyapunov stability analysis shows that the attitude tracking performance is ensured and all signals of the closed-loop system remain bounded. Finally, simulative and experimental results are carried out to illustrate, compared with other observer-based controller, the effectiveness of the proposed method is better.

Sliding Mode Control-Based Autonomous Control of a Tri-rotor Unmanned Aerial Vehicle

2021 ◽  
Vol 01 (03) ◽  
Author(s):  
Abid Raza ◽  
Fahad Mumtaz Malik ◽  
Rameez Khan ◽  
Naveed Mazhar ◽  
Hameed Ullah ◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Unmanned Aerial Vehicle ◽  
Sliding Mode ◽  
Autonomous Control ◽  
Control Technique ◽  
External Disturbances ◽  
Mode Control ◽  
Affine Model ◽  
Highly Nonlinear ◽  
Aerial Vehicle

A nonlinear control technique for autonomous control of a tri-rotor unmanned aerial vehicle is presented in this paper. First, a comprehensive mathematical model is developed using the Newton–Euler approach for a tri-rotor, which is found to be highly nonlinear and coupled. Then, the equivalent input affine model is extracted by applying a suitable transformation. Finally, the sliding mode control for trajectory tracking is chosen which is immune to matched external disturbances, parametric uncertainties, and modeling errors. The proposed controller performance has been verified for appropriate inputs under wind disturbances using MATLAB, and the simulation results are presented.

scholarly journals Robust fault diagnosis and fault-tolerant control for nonlinear quadrotor unmanned aerial vehicle system with unknown actuator faults

2021 ◽  
Vol 18 (2) ◽  
pp. 172988142110027
Author(s):  
Jinjin Guo ◽  
Juntong Qi ◽  
Chong Wu
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Small Amplitude ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Adaptive Observer ◽  
Fault Estimation ◽  
Detection Accuracy ◽  
Actuator Faults ◽  
Model Uncertainties ◽  
Aerial Vehicle

This article addresses the problem that quadrotor unmanned aerial vehicle (UAV) actuator faults, including small-amplitude bias faults and gain degradation, cannot be detected in time. A hybrid observer, which combines the fast convergence from adaptive observer and the strong robustness from sliding mode observer, is proposed to detect and estimate UAV actuator faults accurately with model uncertainties and disturbances. A nonlinear quadrotor UAV model with model uncertainties and disturbances is considered and a more precise unified expression for actuator faults that do not require knowing where the upper or lower bound is provided. The original system is decomposed into two subsystems by coordinate transformation to improve detection accuracy for small amplitude bias faults and avoid external influences. The hybrid observer is then designed to estimate subsystem states and faults with good stability by selecting a Lyapunov function. A fault-tolerant controller is obtained depending on fault estimation by compensating the normal controller (proportion integral differential [PID] controller). Several numerical simulations confirmed that unknown actuator faults can be accurately detected, estimated, and compensated for even under disturbance conditions.

scholarly journals A Novel Adaptive Super-Twisting Sliding Mode Control Scheme with Time-Delay Estimation for a Single Ducted-Fan Unmanned Aerial Vehicle

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 54
Author(s):  
Minh-Thien Tran ◽  
Dong-Hun Lee ◽  
Soumayya Chakir ◽  
Young-Bok Kim
Keyword(s):  
Time Delay ◽  
Sliding Mode Control ◽  
Unmanned Aerial Vehicle ◽  
Sliding Mode ◽  
Time Delay Estimation ◽  
Delay Estimation ◽  
Mode Control ◽  
Ducted Fan ◽  
Control Scheme ◽  
Aerial Vehicle

This article proposes a novel adaptive super-twisting sliding mode control scheme with a time-delay estimation technique (ASTSMC-TDE) to control the yaw angle of a single ducted-fan unmanned aerial vehicle system. Such systems are highly nonlinear; hence, the proposed control scheme is a combination of several control schemes; super-twisting sliding mode, TDE technique to estimate the nonlinear factors of the system, and an adaptive sliding mode. The tracking error of the ASTSMC-TDE is guaranteed to be uniformly ultimately bounded using Lyapunov stability theory. Moreover, to enhance the versatility and the practical feasibility of the proposed control scheme, a comparison study between the proposed controller and a proportional-integral-derivative controller (PID) is conducted. The comparison is achieved through two different scenarios: a normal mode and an abnormal mode. Simulation and experimental tests are carried out to provide an in-depth investigation of the performance of the proposed ASTSMC-TDE control system.

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