Neural Network Indirect Adaptive Sliding Mode Tracking Control for a Class of Nonlinear Interconnected Systems

2005 ◽  
pp. 283-291
Author(s):  
Yanxin Zhang ◽  
Xiaofan Wang
Keyword(s):  
Neural Network ◽  
Tracking Control ◽  
Sliding Mode ◽  
Interconnected Systems ◽  
Adaptive Sliding Mode ◽  
Mode Tracking

Flatness-based adaptive sliding mode tracking control for a quadrotor with disturbances

2018 ◽  
Vol 355 (14) ◽  
pp. 6300-6322 ◽  
Author(s):  
Dailiang Ma ◽  
Yuanqing Xia ◽  
Ganghui Shen ◽  
Zhiqiang Jia ◽  
Tianya Li
Keyword(s):  
Tracking Control ◽  
Sliding Mode ◽  
Adaptive Sliding Mode ◽  
Mode 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.

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