Robust Adaptive Tracking Synchronization Protocols for Leader-follower Multirotor Aerial Vehicles with Uncertainty

2019 ◽  
Author(s):  
Shafiqul Islam ◽  
Abdulmotaleb El Saddik ◽  
Anderson Sunda-Meya
Keyword(s):  
Adaptive Tracking ◽  
Aerial Vehicles ◽  
Robust Adaptive ◽  
Tracking Synchronization

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.

scholarly journals Robust adaptive tracking for Markovian jump nonlinear systems with unknown nonlinearities

2006 ◽  
Vol 2006 ◽  
pp. 1-18 ◽  
Author(s):  
Jin Zhu ◽  
Hong-Sheng Xi ◽  
Hai-Bo Ji ◽  
Bing Wang
Keyword(s):  
Tracking Error ◽  
Small Neighborhood ◽  
Parametric Uncertainty ◽  
Control Law ◽  
Fourth Moment ◽  
Closed Loop System ◽  
Markovian Jump ◽  
Adaptive Tracking ◽  
Adaptive Law ◽  
Robust Adaptive

Robust adaptive tracking problems for a class of Markovian jump parametric-strict-feed-back systems with both parametric uncertainty and unknown nonlinearity are investigated. The unknown nonlinearities considered herein lie within some “bounding functions,” which are assumed to be partially known. By using a stochastic Lyapunov method and backstepping techniques, a parameter adaptive law and a control law were obtained, which guarantee that the tracking error could be within a small neighborhood around the origin in the sense of the fourth moment. Moreover, all signals of the closed-loop system could be globally uniformly ultimately bounded.

Robust adaptive tracking for nonlinear systems using dynamic neural networks

1999 ◽  
Vol 32 (2) ◽  
pp. 4476-4481
Author(s):  
Dai Qionghai ◽  
Wu Hongwei ◽  
Sun Fuxin ◽  
Li Yanda ◽  
Wang Wei ◽  
...  
Keyword(s):  
Neural Networks ◽  
Nonlinear Systems ◽  
Dynamic Neural Networks ◽  
Adaptive Tracking ◽  
Robust Adaptive
Sign in / Sign up

Export Citation Format

Share Document