Robust trajectory tracking controller for quadrotor helicopter based on a novel composite control scheme

2019 ◽  
Vol 85 ◽  
pp. 199-215 ◽  
Author(s):  
Juqian Zhang ◽  
Dawei Gu ◽  
Zhaohui Ren ◽  
Bangchun Wen
Processes ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1951
Author(s):  
Shun-Hung Tsai ◽  
Yi-Ping Chang ◽  
Hung-Yi Lin ◽  
Luh-Maan Chang

A robust trajectory tracking control scheme for quadrotor unmanned aircraft vehicles under uncertainties is proposed herein. A tracking controller combined with the sliding mode and integral backstepping is performed for position and attitude tracking. The stability of the trajectory tracking controller of the quadrotor is investigated via Lyapunov stability analysis. By incorporating force and torque disturbances into numerical simulations, the results demonstrate the effectiveness of the proposed quadrotor trajectory controller. Finally, the experiments validate the feasibility of the proposed controller.


2018 ◽  
Vol 42 (3) ◽  
pp. 239-251
Author(s):  
Li Ding ◽  
Jinyu Zhou ◽  
Wentao Shan

This article addresses the problem of designing and experimentally validating a controller for steering an unmanned hexrotor along a trajectory while rejecting the lumped disturbance. Based on the developed nonlinear dynamical model, a hybrid high-performance trajectory tracking controller is designed. In this control scheme, a linear active disturbance rejection control technology is introduced to stabilize the attitude loop, and an integral backstepping control methodology is employed to control the position loop. Subsequently, the performance of the proposed flight control strategy is tested in a simulation environment. The developed algorithms are then transplanted to a real system. A prototype and a flight experiment are established to verify its effectiveness. Experimental results are presented to show that the actual trajectory closely matches well with the ideal one. It demonstrates that the proposed controller provides good performance and robustness.


Author(s):  
Cassius Z. Resende ◽  
F. Espinosa ◽  
I. Bravo ◽  
Mario Sarcinelli-Filho ◽  
Teodiano F. Bastos-Filho

Author(s):  
Pouya Panahandeh ◽  
Khalil Alipour ◽  
Bahram Tarvirdizadeh ◽  
Alireza Hadi

Purpose Trajectory tracking is a common problem in the field of mobile robots which has attracted a lot of attention in the past two decades. Therefore, besides the search for new controllers to achieve a better performance, improvement and optimization of existing control rules are necessary. Trajectory tracking control laws usually contain constant gains which affect greatly the robot’s performance. Design/methodology/approach In this paper, a method based on neural networks is introduced to automatically upgrade the gains of a well-known trajectory tracking controller of wheeled mobile robots. The suggested method speeds up the convergence rate of the main controller. Findings Simulations and experiments are performed to assess the ability of the suggested scheme. The obtained results show the effectiveness of the proposed method. Originality/value In this paper, a method based on neural networks is introduced to automatically upgrade the gains of a well-known trajectory tracking controller of wheeled mobile robots. The suggested method speeds up the convergence rate of the main controller.


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