Suboptimal Integral Sliding Mode Trajectory Tracking Control of a UAV Based on SDRE Method

2021 ◽  
pp. 67-77
Author(s):  
Zheng Hua
Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Jiawen Cui ◽  
Haibin Sun

The issue of fixed-time trajectory tracking control for the autonomous surface vehicles (ASVs) system with model uncertainties and external disturbances is investigated in this paper. Particularly, convergence time does not depend on initial conditions. The major contributions include the following: (1) An integral sliding mode controller (ISMC) via integral sliding mode surface is first proposed, which can ensure that the system states can follow the desired trajectory within a fixed time. (2) Unknown external disturbances are absolutely estimated by means of designing a fixed-time disturbance observer (FTDO). By combining the FTDO and ISMC techniques, a new control scheme (FTDO-ISMC) is developed, which can achieve both disturbance compensation and chattering-free condition. (3) Aiming at reconstructing the unknown nonlinear dynamics and external disturbances, a fixed-time unknown observer (FTUO) is proposed, thus providing the FTUO-ISMC scheme that finally achieves trajectory tracking of ASVs with unknown parameters. Finally, simulation tests and detailed comparisons indicate the effectiveness of the proposed control scheme.


Author(s):  
Anh Tuan Vo ◽  
Ngoc Hoai An Nguyen ◽  
Duy Duong Pham

This paper proposes an integral sliding mode for trajectory tracking control of robotic manipulators. Our proposed control method is developed on the foundation of the benefits in both integral sliding mode control and adaptive twisting control algorithm, such as high robustness, high accuracy, estimation ability, and chattering elimination. In this paper, the proposed integral sliding mode controller is designed with the elimination of the reaching phase to offer better trajectory tracking precision and to stabilize the robot system. To reduce the calculation burden along with chattering rejection, an adaptive twisting controller with only one simple adaptive rule is employed to estimate the upper-boundary values of the lumped uncertainties. Accordingly, the requirement of their prior knowledge is removed and then decrease the computation complexity. Consequently, this control method provides better trajectory tracking accuracy to handle the dynamic uncertainties and external disturbances more strongly. The system global stability of the control system is guaranteed by using Lyapunov criteria. Finally, simulated examples are performed to analyze the effectiveness of our control approach for position pathway tracking control of a 2-DOF parallel manipulator.


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