Fault Diagnosis of Electro-hydraulic Position Servo Closed-loop System Based on Support Vector Regression

2007 ◽  
Author(s):  
Keqiang Cao ◽  
Jianbang Zhang ◽  
Liangmou Hu
Keyword(s):  
Fault Diagnosis ◽  
Support Vector Regression ◽  
Closed Loop ◽  
Loop System ◽  
Support Vector ◽  
Closed Loop System ◽  
Position Servo

Robust adaptive command filtered control of a robotic manipulator with uncertain dynamic and joint space constraints

Robotica ◽  
2018 ◽  
Vol 36 (5) ◽  
pp. 767-786 ◽  
Author(s):  
Joseph Jean-Baptiste Mvogo Ahanda ◽  
Jean Bosco Mbede ◽  
Achille Melingui ◽  
Bernard Essimbi Zobo
Keyword(s):  
Closed Loop ◽  
Robotic Manipulator ◽  
Joint Space ◽  
Robust Adaptive Control ◽  
Lyapunov Theory ◽  
Loop System ◽  
Support Vector ◽  
Closed Loop System ◽  
Uncertain Dynamics ◽  
Robust Adaptive

SUMMARYThe problem of robust adaptive control of a robotic manipulator subjected to uncertain dynamics and joint space constraints is addressed in this paper. Command filters are used to overcome the time derivatives of virtual control, thus reducing the need for desired trajectory differentiations. A barrier Lyapunov function is used to deal with the joint space constraints. A robust adaptive support vector regression architecture is used to reduce filtering errors, approximation errors and handle dynamic uncertainties. The stability analysis of the closed-loop system using the Lyapunov theory permits to highlight adaptation laws and to prove that all signals of the closed-loop system are bounded. Simulations show the effectiveness of the proposed control strategy.

Robust adaptive control for robot manipulators: Support vector regression-based command filtered adaptive backstepping approach

Robotica ◽  
2017 ◽  
Vol 36 (4) ◽  
pp. 516-534 ◽  
Author(s):  
Joseph Jean-Baptiste Mvogo Ahanda ◽  
Jean Bosco Mbede ◽  
Achille Melingui ◽  
Bernard Essimbi
Keyword(s):  
Adaptive Control ◽  
Support Vector Regression ◽  
Closed Loop ◽  
Robot Manipulators ◽  
Robust Adaptive Control ◽  
Support Vector ◽  
Closed Loop System ◽  
Adaptive Backstepping ◽  
Backstepping Approach ◽  
Robust Adaptive

SUMMARYThis study derives a robust adaptive control of electrically driven robot manipulators using a support vector regression (SVR)-based command filtered adaptive backstepping approach. The robot system is supposed to be subject to model uncertainties, neglected dynamics, and external disturbances. The command filtered backstepping algorithm is extended to the case of the robot manipulators. A robust term is added to the common adaptive SVR algorithm, to mitigate the effects of the SVR approximation error in the path tracking performance. The stability analysis of the closed loop system using the Lyapunov theory permits to highlight adaptation laws and to prove that all the signals in the closed loop system are bounded. Simulations show the effectiveness of the proposed control strategy.

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