An unsupervised neural network for low-level control of a wheeled mobile robot: noise resistance, stability, and hardware implementation

1996 ◽  
Vol 26 (3) ◽  
pp. 485-496 ◽  
Author(s):  
P. Gaudiano ◽  
E. Zalama ◽  
J.L. Coronado
Keyword(s):  
Neural Network ◽  
Mobile Robot ◽  
Hardware Implementation ◽  
Wheeled Mobile Robot ◽  
Level Control ◽  
Noise Resistance ◽  
Low Level ◽  
Unsupervised Neural Network ◽  
Resistance Stability

An Exponential Decreased Kinematic and PID Low Level Control Schemes for an Omni-Wheeled Mobile Robot

2021 ◽  
Author(s):  
Indrazno Siradjuddin ◽  
Totok Winarno ◽  
Muhammad Khairuddin ◽  
Mas Nurul Achmadiah ◽  
Rendi Pambudi Wicaksono ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Wheeled Mobile Robot ◽  
Level Control ◽  
Low Level ◽  
Control Schemes

scholarly journals DESIGNING A ROBUST ADAPTIVE TRACKING BACKTEPPING CONTROLLER CONSIDERING ACTUATOR SATURATION FOR A WHEELED MOBILE ROBOT TO COMPENSATE UNKNOWN SLIPPAGE

2020 ◽  
Vol 36 (2) ◽  
pp. 187-204
Author(s):  
Chung Le ◽  
Kiem Nguyen Tien ◽  
Linh Nguyen ◽  
Tinh Nguyen ◽  
Tung Hoang
Keyword(s):  
Neural Network ◽  
Mobile Robot ◽  
Basis Function ◽  
Actuator Saturation ◽  
Wheeled Mobile Robot ◽  
Technical Solution ◽  
Control Approach ◽  
Adaptive Tracking ◽  
Simulation Results ◽  
Robust Adaptive

This article highlights a robust adaptive tracking backstepping control approach for a nonholonomic wheeled mobile robot (WMR) by which the bad problems of both unknown slippage and uncertainties are dealt with. The radial basis function neural network (RBFNN) in this proposed controller assists unknown smooth nonlinear dynamic functions to be approximated. Furthermore, a technical solution is also carried out to avoid actuator saturation. The validity and efficiency of this novel controller, finally, are illustrated via comparative simulation results.

Sign in / Sign up

Export Citation Format

Share Document