On the trajectory tracking control of industrial SCARA robot manipulators

2002 ◽  
Vol 49 (1) ◽  
pp. 224-232 ◽  
Author(s):  
A. Visioli ◽  
G. Legnani
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Robot Manipulators ◽  
Trajectory Tracking Control ◽  
Scara Robot

Trajectory tracking control of robot manipulators using a neural-network-based torque compensator

1998 ◽  
Vol 212 (5) ◽  
pp. 361-372 ◽  
Author(s):  
Q Li ◽  
S K Tso ◽  
W J Zhang
Keyword(s):  
Neural Network ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
High Performance ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Lyapunov Stability Theory ◽  
System Stability ◽  
Trajectory Tracking Control ◽  
Modelling Uncertainties

In this paper, an adaptive neural-network-based torque compensator is developed for the trajectory-tracking control of robot manipulators. The overall control structure employs a classical non-linear decoupling controller for actuating torque computation based on an approximated robot dynamic model. To suppress the effects of uncertainties associated with the estimated model, a supplementary neural network algorithm is developed to generate compensation torques. The weight adaptation rule for this neuro-compensator is derived on the basis of the Lyapunov stability theory. Both global system stability and the error convergence can then be guaranteed. Simulation studies on a two-link robot manipulator demonstrate that high performance of the proposed control algorithm could be achieved under severe modelling uncertainties.

scholarly journals ARGESIM Benchmark C11 'SCARA Robot’ with Extended Trajectory Tracking Control

2021 ◽  
Vol 31 (1) ◽  
pp. 43-51
Author(s):  
Martin Batliner ◽  
Felix Breitenecker ◽  
Andreas Körner ◽  
Horst Ecker
Keyword(s):  
Trajectory Tracking ◽  
Tracking Control ◽  
Trajectory Tracking Control ◽  
Scara Robot
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