scholarly journals Experimental Results of Trajectory Tracking Control of Robot Manipulator using Time Varying Sliding Mode Controller

Author(s):  
Yasuhiko Mutoh ◽  
Nao Kogure
Author(s):  
Monisha Pathak ◽  
◽  
Mrinal Buragohain ◽  

In this paper a New RBF Neural Network based Sliding Mode Adaptive Controller (NNNSMAC) for Robot Manipulator trajectory tracking in the presence of uncertainties and disturbances is introduced. The research offers a learning with minimal parameter (LMP) technique for robotic manipulator trajectory tracking. The technique decreases the online adaptive parameters number in the RBF Neural Network to only one, lowering computational costs and boosting real-time performance. The RBFNN analyses the system's hidden non-linearities, and its weight value parameters are updated online using adaptive laws to control the nonlinear system's output to track a specific trajectory. The RBF model is used to create a Lyapunov function-based adaptive control law. The effectiveness of the designed NNNSMAC is demonstrated by simulation results of trajectory tracking control of a 2 dof Robotic Manipulator. The chattering effect has been significantly reduced.


Robotica ◽  
2016 ◽  
Vol 35 (10) ◽  
pp. 2036-2055 ◽  
Author(s):  
Ahmet Dumlu ◽  
Köksal Erentürk ◽  
Alirıza Kaleli ◽  
Kağan Koray Ayten

SUMMARYIn this paper, design, analysis and real-time trajectory tracking control of a 6-degree of freedom revolute spherical-spherical type parallel manipulator, actuated by six hybrid stepper motors, has been studied. Two different control approaches have been used to improve the trajectory tracking performance of the designed manipulator. The first approach considered a single input-single output (SISO) linear quadratic regulator (LQR) for trajectory tracking control of the manipulator. Another controller type based on a nonlinear sliding mode controller method has been utilized to take decoupled dynamic approximation model of the manipulator into account and to improve tracking performance of the manipulator. Real-time experimental results for the two different control techniques have been verified. Finally, according to the results, the nonlinear sliding mode controller method has improved the tracking performance of the designed manipulator.


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