scholarly journals RBFNN based adaptive control of uncertain robot manipulators in discrete time

2016 ◽  
Author(s):  
Runxian Yang ◽  
Chenguang Yang ◽  
Mou Chen ◽  
Jing Na
Keyword(s):  
Adaptive Control ◽  
Discrete Time ◽  
Robot Manipulators ◽  
Uncertain Robot

Consensus in networks of uncertain robot manipulators without using neighbors’ velocity information

Robotica ◽  
2021 ◽  
pp. 1-17
Author(s):  
Seyed Mostafa Almodarresi ◽  
Marzieh Kamali ◽  
Farid Sheikholeslam
Keyword(s):  
Information Exchange ◽  
Lyapunov Functions ◽  
Robot Manipulators ◽  
Adaptive Methods ◽  
Convergence Time ◽  
Parameter Search ◽  
Velocity Information ◽  
Simulation Results ◽  
Uncertain Robot ◽  
Asymptotic Synchronization

Abstract In this paper, new distributed adaptive methods are proposed for solving both leaderless and leader–follower consensus problems in networks of uncertain robot manipulators, by estimating only the gravitational torque forces. Comparing with the existing adaptive methods, which require the estimation of the whole dynamics, presented methods reduce the excitation levels required for efficient parameter search, the convergence time, and the complexity of the regressor. Additionally, proposed schemes eliminate the need for velocity information exchange between the agents. Global asymptotic synchronization is shown by introducing new Lyapunov functions. Simulation results are provided for a network of 10 4-DOF robot manipulators.

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