Generic Adaptive Sliding Mode Control for a Quadrotor UAV System Subject to Severe Parametric Uncertainties and Fully Unknown External Disturbance

2020 ◽  
Author(s):  
Tianpeng Huang ◽  
Deqing Huang ◽  
Zhikai Wang ◽  
Xi Dai ◽  
Awais Shah
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
External Disturbance ◽  
Adaptive Sliding Mode Control ◽  
Parametric Uncertainties ◽  
Adaptive Sliding Mode ◽  
Quadrotor Uav ◽  
Mode Control

Adaptive Sliding Mode Control of MEMS Vibrational Gyroscope

2006 ◽  
Author(s):  
J. Fei ◽  
C. Batur
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
Angular Rate ◽  
External Disturbance ◽  
Adaptive Sliding Mode Control ◽  
Angular Velocity Vector ◽  
Adaptive Sliding Mode ◽  
Mode Control ◽  
Control Scheme ◽  
On Line

This paper presents a new sliding mode adaptive controller for MEMS z-axis gyroscope. The proposed adaptive sliding mode control algorithm can on-line estimate the component of the angular velocity vector, which is orthogonal to the plane of oscillation of the gyroscope (the z-axis) and the linear damping and stiffness model coefficients. The stability of the closed-loop system can be guaranteed with the proposed control strategy. The numerical simulation for MEMS Gyroscope is investigated to verify the effectiveness of the proposed adaptive sliding mode control scheme. It is shown that the proposed adaptive sliding mode control scheme offers several advantages such as on-line estimation of gyroscope parameters including angular rate and large robustness to parameter variations and external disturbance.

scholarly journals Adaptive Sliding Mode Control for a Robotic Manipulator with Unknown Friction and Unknown Control Direction

2021 ◽  
Vol 11 (9) ◽  
pp. 3919
Author(s):  
Seung-Hun Han ◽  
Manh Son Tran ◽  
Duc-Thien Tran
Keyword(s):  
Sliding Mode Control ◽  
Sliding Mode ◽  
External Disturbance ◽  
Adaptive Sliding Mode Control ◽  
Adaptive Sliding Mode ◽  
Mode Control ◽  
Nussbaum Function ◽  
Unknown Control ◽  
Unknown Control Direction ◽  
Control Direction

This paper is aimed at addressing the tracking control issue for an n-DOF manipulator regardless of unknown friction and unknown control direction. In order to handle the above issues, an adaptive sliding mode control (ASMC) is developed with a Nussbaum function. The sliding mode control (SMC) in the proposed control guarantees the tracking problem and fast responses for the manipulator. Additionally, there are adaptive laws for the robust gain in the SMC to deal with the unknown external disturbance and reduce the chattering effect in the system. In practice, the mistakes in the connection between actuators and drivers, named unknown control direction, cause serious damage to the manipulator. To overcome this issue, the Nussbaum function is multiplied by the ASMC law. A Lyapunov approach is investigated to analyze the stability and robustness of the whole system. Finally, several simulations are implemented on a 3-DOF manipulator and their results are compared with those of the existing controllers to validate the advantages of the proposed method.

scholarly journals Research on Variable Cycle Engine Control Based on Model Reference Adaptive Sliding Mode Control Method

2018 ◽  
Vol 36 (5) ◽  
pp. 824-830
Author(s):  
Hongliang Xiao ◽  
Huacong Li ◽  
Jia Li ◽  
Jiangfeng Fu ◽  
Kai Peng
Keyword(s):  
Sliding Mode Control ◽  
Control Method ◽  
Sliding Mode ◽  
External Disturbance ◽  
Adaptive Sliding Mode Control ◽  
Engine Control ◽  
Model Reference ◽  
Adaptive Sliding Mode ◽  
Mode Control ◽  
Model Reference Adaptive

As to solve the problem of multivariable output tracking control of variable cycle engine under system uncertainties and external disturbances, an augmented model reference adaptive sliding mode control method based on LQR method was developed. Firstly, the model is augmented and the reference state is provided to the controller by designing the reference model using the optimal LQR method. Then, based on the state tracking sliding mode control method, the adaptive law is derived based on the strict stability condition of Lyapunov function to estimate the upper bound of the system perturbation matrix and the upper bound of the external disturbances. Finally, the controller achieves the asymptotic zero tracking error of the system under the conditions of uncertainty and external disturbance. The simulation results showed that the LQR-based augmented model reference adaptive sliding mode control method can solve the problem that the traditional sliding mode control method needs to specify the reference state in advance and improve the control performance of the variable cycle engine control with system uncertainties and external disturbance. The tracking of the control command is effectively achieved and the steady-state and dynamic performance are improved. The steady-state control errors under different conditions are less than 0.1%, the system overshoot is less than 0.5%, and the adjustment time is less than 1s, which conformed to the requirements of the aero engine control system technology.

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