scholarly journals Modified Adaptive Sliding Mode Control for Trajectory Tracking of Mini-drone Quadcopter Unmanned Aerial Vehicle

2020 ◽  
Vol 13 (5) ◽  
pp. 145-158
Author(s):  
Jutarut Chaoraingern ◽  
◽  
Vittaya Tipsuwanporn ◽  
Arjin Numsomran ◽  
◽  
...  
Keyword(s):  
Sliding Mode Control ◽  
Unmanned Aerial Vehicle ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Adaptive Sliding Mode Control ◽  
Adaptive Sliding Mode ◽  
Mode Control ◽  
Aerial Vehicle

Adaptive Sliding Mode Control for Depth Trajectory Tracking of Remotely Operated Vehicle with Thruster Nonlinearity

2016 ◽  
Vol 70 (1) ◽  
pp. 149-164 ◽  
Author(s):  
Zhenzhong Chu ◽  
Daqi Zhu ◽  
Simon X. Yang ◽  
Gene Eu Jan
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Sliding Mode ◽  
Dead Zone ◽  
Adaptive Sliding Mode Control ◽  
Remotely Operated Vehicle ◽  
Trajectory Tracking Control ◽  
Adaptive Sliding Mode ◽  
Saturation Nonlinearity ◽  
Mode Control

This paper focuses on depth trajectory tracking control for a Remotely Operated Vehicle (ROV) with dead-zone nonlinearity and saturation nonlinearity of thruster; an adaptive sliding mode control method based on neural network is proposed. Through the analysis of dead-zone nonlinearity and saturation nonlinearity of thruster, the depth trajectory tracking control system model of a ROV which uses thruster control signals as system input has been established. According to the principle of sliding mode control, an adaptive sliding mode depth trajectory tracking controller is built by using three-layer feed-forward neural network for online identification of unknown items. The selection method and update laws of the control parameters are also given. The uniform ultimate boundedness of trajectory tracking error is analysed by Lyapunov theorem. Finally, the effectiveness of the proposed method is illustrated by simulations.

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