On adaptive sliding mode control for improved quadrotor tracking

2017 ◽  
Vol 24 (14) ◽  
pp. 3219-3230 ◽  
Author(s):  
Sudhir Nadda ◽  
A Swarup

The tracking control of a quadrotor has been considered in this paper. The application of sliding mode control provides robustness against parametric uncertainties, but it requires knowledge of the upper bounds of uncertainties. An adaptation strategy has been proposed to implement sliding mode control, which does not require the upper bound of the uncertainties. The adaptive control law is derived on the basis of Lyapunov stability theory, which guarantees the tracking performance. The adaptation can be tuned faster by proper tuning, and convergence with good tracking can be achieved. The proposed adaptive method has improved robustness and provided simpler implementation. Through an illustrative simulation example, the performance of the proposed control method is presented and also compared with classical sliding mode control from the literature. It is demonstrated that the performance of quadrotor altitude tracking and convergence has been considerably improved while maintaining stability, even in presence of external disturbances and parameter uncertainties.

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Guangshi Li

In this paper, an adaptive sliding mode control method based on neural networks is presented for a class of manipulator systems. The main characteristic of the discussed system is that the output variable is required to keep within a constraint set. In order to ensure that the system output meets the time-varying constraint condition, the asymmetric barrier Lyapunov function is selected in the design process. According to Lyapunov stability theory, the stability of the closed-loop system is analyzed. It is demonstrated that all signals in the resulted system are bounded, the tracking error converges to a small compact set, and the system output limits in its constrained set. Finally, the simulation example is used to show the effectiveness of the presented control strategy.


2019 ◽  
Vol 16 (5) ◽  
pp. 172988141988152
Author(s):  
Bai Rui

Recent years, electronically controlled air suspension has been widely used in vehicles to improve the riding comfort and the road holding ability. This article presents a new nonlinear adaptive sliding-mode control method for electronically controlled air suspension. A nonlinear dynamical model of electronically controlled air suspension is established, where the nonlinear dynamical characteristic of the air spring is considered. Based on the proposed nonlinear dynamic model, an adaptive sliding-mode control method is presented to stabilize the displacement of electronically controlled air suspension in the presence of parameter uncertainties. Parameter adaptive laws are designed to estimate the unknown parameters in electronically controlled air suspension. Stability analysis of the proposed nonlinear adaptive sliding-mode control method is given using Lyapunov stability theory. At last, the reliability of the proposed control method is evaluated by the computer simulation. Simulation research shows that the proposed control method can obtain the satisfactory control performance for electronically controlled air suspension.


2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Wafaa Jawaada ◽  
M. S. M. Noorani ◽  
M. Mossa Al-sawalha

The antisynchronization behavior of chaotic systems with parametric uncertainties and external disturbances is explored by using robust active sliding mode control method. The sufficient conditions for achieving robust antisynchronization of two identical chaotic systems with different initial conditions and two different chaotic systems with terms of uncertainties and external disturbances are derived based on the Lyapunov stability theory. Analysis and numerical simulations are shown for validation purposes.


2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Hongliang Xiao ◽  
Huacong Li ◽  
Kai Peng ◽  
Jia Li

Abstract In this paper, a model reference adaptive sliding mode control method is proposed for a variable cycle engine (VCE) which is a MIMO system with uncertainties and external disturbances. The reference model is designed based on optimal LQR method to provide ideal reference states. An adaptive sliding mode controller (ASMC) is designed for model reference adaptive control structure, which the adaptive law is derived based on Lyapunov function to estimate the unknown upper bound of uncertainties and external disturbances. Simulation results for VCE demonstrate the performance and fidelity of the proposed method.


Author(s):  
Cong Cheng ◽  
◽  
Ru Lai ◽  
Zhen Chen ◽  
Xiangdong Liu

This paper presents an adaptive nonsingular terminal sliding mode control algorithm with a modified switch function for a 6-DOF manipulator with unknown modeling errors and external disturbances. The finitetime convergence of the controller is analyzed using Lyapunov stability theory. The algorithm avoids singular problems and estimates the upper bound of system uncertainties. A modified switch function is used to achieve precise tracking and reduce chattering in control torque. Finally, the effectiveness of the control method is verified through simulation.


2020 ◽  
Vol 10 (14) ◽  
pp. 4779 ◽  
Author(s):  
Cheng Lu ◽  
Liang Hua ◽  
Xinsong Zhang ◽  
Huiming Wang ◽  
Yunxiang Guo

This paper investigates one kind of high performance control methods for Micro-Electro-Mechanical-System (MEMS) gyroscopes using adaptive sliding mode control (ASMC) scheme with prescribed performance. Prescribed performance control (PPC) method is combined with conventional ASMC method to provide quantitative analysis of gyroscope tracking error performances in terms of specified tracking error bound and specified error convergence rate. The new derived adaptive prescribed performance sliding mode control (APPSMC) can maintain a satisfactory control performance which guarantees system tracking error, at any time, to be within a predefined error bound and the error convergences faster than the error bound. Besides, adaptive control (AC) technique is integrated with PPC to online tune controller parameters, which will converge to their true values at last. The stability of the control system is proved in the Lyapunov stability framework and simulation results on a Z-axis MEMS gyroscope is conducted to validate the effectiveness of the proposed control approach.


2013 ◽  
Vol 321-324 ◽  
pp. 1704-1707
Author(s):  
Qing Hu ◽  
Hong Bin Du ◽  
Dong Mei Yu

For external disturbances and parameter perturbation problem of Electromagnetic guiding system, the adaptive sliding mode control method is used, take advantage of sliding mode switching surface eliminate the steady-state error and increase the precision at steady-state and robust performance of single electromagnetic guiding system. Matlab Simulation results show that the proposed control strategy shows good tracking performance and strong robustness


2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Ehsan Maani Miandoab ◽  
Aghil Yousefi-Koma ◽  
Saeed Hashemnia

Two different control methods, namely, adaptive sliding mode control and impulse damper, are used to control the chaotic vibration of a block on a belt system due to the rate-dependent friction. In the first method, using the sliding mode control technique and based on the Lyapunov stability theory, a sliding surface is determined, and an adaptive control law is established which stabilizes the chaotic response of the system. In the second control method, the vibration of this system is controlled by an impulse damper. In this method, an impulsive force is applied to the system by expanding and contracting the PZT stack according to efficient control law. Numerical simulations demonstrate the effectiveness of both methods in controlling the chaotic vibration of the system. It is shown that the settling time of the controlled system using impulse damper is less than that one controlled by adaptive sliding mode control; however, it needs more control effort.


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