Robust nonlinear tracking control design for IPMC using Neural Network based sliding mode approach

2014 ◽  
Author(s):  
Dongyun Wang ◽  
Qiang Zhang ◽  
Aihui Wang ◽  
Tongbin Yan
Keyword(s):  
Neural Network ◽  
Tracking Control ◽  
Sliding Mode ◽  
Control Design ◽  
Nonlinear Tracking

scholarly journals Sliding Mode with Adaptive Control of Robot Manipulator Trajectory Tracking using Neural Network Approximation

2021 ◽  
Vol 10 (6) ◽  
pp. 120
Author(s):  
Monisha Pathak* ◽  
◽  
Dr. Mrinal Buragohain ◽  
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Robotic Manipulator ◽  
Adaptive Sliding Mode Control ◽  
Control Approach ◽  
Adaptive Sliding Mode

This paper briefly discusses about the Robust Controller based on Adaptive Sliding Mode Technique with RBF Neural Network (ASMCNN) for Robotic Manipulator tracking control in presence of uncertainities and disturbances. The aim is to design an effective trajectory tracking controller without any modelling information. The ASMCNN is designed to have robust trajectory tracking of Robot Manipulator, which combines Neural Network Estimation with Adaptive Sliding Mode Control. The RBF model is utilised to construct a Lyapunov function-based adaptive control approach. Simulation of the tracking control of a 2dof Robotic Manipulator in the presence of unpredictability and external disruption demonstrates the usefulness of the planned ASMCNN.

scholarly journals TRACKING CONTROL DESIGN USING SLIDING MODE TECHNIQUES FOR SATELLITE FORMATION FLYING

2003 ◽  
Vol 20 (4) ◽  
pp. 365-374 ◽  
Author(s):  
Hyung-Chul Lim ◽  
Hyo-Choong Bang ◽  
Kwan-Dong Park ◽  
Pil-Ho Park
Keyword(s):  
Tracking Control ◽  
Formation Flying ◽  
Sliding Mode ◽  
Control Design ◽  
Satellite Formation Flying ◽  
Satellite Formation
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