Suboptimal Integral Sliding Mode Attitude Control of a Unmanned Aerial Vehicle Under Input Saturation

2018 ◽  
Author(s):  
Hua Zheng ◽  
Donghui Wang ◽  
Haijun Zhou ◽  
Huaizhe Liu ◽  
Bin Lyu ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Attitude Control ◽  
Sliding Mode ◽  
Input Saturation ◽  
Integral Sliding Mode ◽  
Aerial Vehicle

Robust linear parameter varying attitude control of a quadrotor unmanned aerial vehicle with state constraints and input saturation subject to wind disturbance

2019 ◽  
Vol 42 (6) ◽  
pp. 1083-1096 ◽  
Author(s):  
Mohammad Reza Soltanpour ◽  
Farshad Hasanvand ◽  
Reza Hooshmand
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Attitude Control ◽  
Input Saturation ◽  
Disturbance Attenuation ◽  
Linear Matrix ◽  
Linear Parameter ◽  
Linear Parameter Varying ◽  
Aerial Vehicle ◽  
Parameter Varying ◽  
Parameter Dependent

In this paper, a gain scheduled [Formula: see text] state-feedback controller has been designed to control the attitude of a linear parameter varying (LPV) model of a quadrotor unmanned aerial vehicle (UAV). The scheduling parameters vector, which consists of some states and the control inputs, must vary in a specified polyhedron so that the affine LPV model would be analyzable; therefore, some pre-assumed constraints on states and input saturation have been taken into account in design process. The stabilization and disturbance attenuation conditions are obtained via elementary manipulations on the notion of [Formula: see text] control design. The resulting parameter dependent linear matrix inequalities are solved through a Robust LMI Parser (Rolmip) – which works jointly with YALMIP (A toolbox for modeling and optimization in MATLAB)– by transforming polynomial parameter dependent matrices into multi-simplex domain, to best deal with nonconvex problems. In the end, simulation results have been presented and compared with existing literature to examine the capability of such method in the presence and absence of wind disturbances.

scholarly journals Trajectory planning of quadrotor using sliding mode control with extended state observer

2020 ◽  
Vol 53 (7-8) ◽  
pp. 1300-1308
Author(s):  
Jun Xiao
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Attitude Control ◽  
Sliding Mode ◽  
State Observer ◽  
Control Model ◽  
Extended State Observer ◽  
Extended State ◽  
Inner Model ◽  
Aerial Vehicle

This paper presents the trajectory planning of an under-actuated quadcopter unmanned aerial vehicle. To control the complete structure of the rotorcraft, the main model is divided into two sub-models, namely inner model and external model. The inner model is for the attitude control model controlled by the sliding mode controller and the outer model is altitude control model governed by the extended state observer. The quadrotor unmanned aerial vehicle is a type of multivariable, multi-degree-of-freedom and nonlinear in nature. Planning the trajectory of the unmanned aerial vehicle and stabilizing its flight are complex tasks because of its ability to maneuver quickly. Due to these stated issues, the tuning of this type of dynamic system is a difficult task. This paper deals with these issues by designing the aforementioned dual controller scheme. In addition, the effectiveness of the proposed controller is apparent in simulations performed in MATLAB, Simulink 2016. The designed controller shows better results and robustness than traditional controllers do.

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.

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.

Anti-disturbance attitude control for quadrotor unmanned aerial vehicle manipulator via fuzzy adaptive sigmoid generalized super-twisting sliding mode observer

2021 ◽  
pp. 107754632198949
Author(s):  
Ran Jiao ◽  
Wusheng Chou ◽  
Yongfeng Rong ◽  
Mingjie Dong
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Attitude Control ◽  
Sliding Mode ◽  
Sliding Mode Observer ◽  
Sliding Mode Controller ◽  
Sigmoid Function ◽  
Tracking Differentiator ◽  
Aerial Vehicle ◽  
Signum Function ◽  
Twisting Algorithm

During the flight of quadrotor unmanned aerial vehicle manipulator, external wind and model uncertainties will significantly affect the accuracy and stability of the controller. This study investigates the problem of high-precision attitude control for the quadrotor manipulator that is equipped with a 2-DOF robotic arm in presence of several disturbances based on a new sliding mode observer and a corresponding sliding mode controller. As for the proposed sliding mode observer, to reduce its estimation chattering phenomenon, a sigmoid function is exploited to replace the discontinuous signum function. Moreover, to adapt to the estimation of disturbances with different upper bounds of the first derivative, a fuzzy logic system algorithm is used to adaptively update the observer gains and slope parameters of the sigmoid function. Furthermore, a generalized super-twisting algorithm is incorporated into the proposed sliding mode observer. Similarly, the sliding mode controller is constructed by using the generalized super-twisting algorithm and a sigmoid function in addition to the sliding mode observer-based feedforward disturbance compensation. In addition, to further relieve the influence of system sensor noise, a tracking differentiator is exploited to incorporate with both proposed sliding mode observer and sliding mode controller. Finally, to demonstrate the effectiveness of the proposed method, several simulations and experiments on the quadrotor unmanned aerial vehicle manipulator system are conducted under varying external disturbances.

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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