robust tracking
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2021 ◽  
Vol 240 ◽  
pp. 109945
Hexiong Zhou ◽  
Jian Fu ◽  
Zheng Zeng ◽  
Caoyang Yu ◽  
Zhaoyu Wei ◽  

Yongpeng Weng ◽  
Dong Nan ◽  
Ning Wang ◽  
Zhuofu Liu ◽  
Zhe Guan

In this paper, the robust trajectory tracking control problem of disturbed quadrotor unmanned aerial vehicles (UAVs) with disturbances, uncertainties and unmodeled dynamics is addressed, by devising a novel compound robust tracking control (CRTC) approach via data-driven cascade control technique. By deploying the data-driven philosophy, a data-based sliding-mode surface is proposed, and thereby contributing to strong adaptability to nonlinearity and model-unknown properties of the UAVs. By utilizing the backstepping technique, virtual control strategy and a novel cascaded compound robust PD control structure, the attitude and position subsystems are efficiently cohered such that a data-driven cascaded compound robust controller containing both PD control and sliding-mode control can be developed to conquer the lumped disturbances induced by uncertainties, disturbances and unmodeled dynamics. Eventually, the asymptotic convergence of the tracking errors with respect to both attitude and position subsystems can be guaranteed rigorously. Simulation studies on a prototype quadrotor UAV are performed to evaluate the efficacy and superiority of the devised CRTC method.

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Yi Wang ◽  
He Ma ◽  
Weidong Wu

This article studies the robust tracking control problems of Euler–Lagrange (EL) systems with uncertainties. To enhance the robustness of the control systems, an asymmetric tan-type barrier Lyapunov function (ATBLF) is used to dynamic constraint position tracking errors. To deal with the problems of the system uncertainties, the self-structuring neural network (SSNN) is developed to estimate the unknown dynamics model and avoid the calculation burden. The robust compensator is designed to estimate and compensate neural network (NN) approximation errors and unknown disturbances. In addition, a relative threshold event-triggered strategy is introduced, which greatly saves communication resources. Under the proposed robust control scheme, tracking behavior can be implemented with disturbance and unknown dynamics of the EL systems. All signals in the closed-loop system are proved to be bounded by stability analysis, and the tracking error can converge to the neighborhood near the origin. The numerical simulation results show the effectiveness and the validity of the proposed robust control scheme.

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