Adaptive gain sliding observer based sliding controller for uncertain parameters nonlinear systems. Application to flexible joint robots

2004 ◽  
Author(s):  
A. Filipescu ◽  
L. Dugard ◽  
J.-M. Dion
Keyword(s):  
Nonlinear Systems ◽  
Uncertain Parameters ◽  
Flexible Joint ◽  
Flexible Joint Robots

scholarly journals Extended and Unscented Kalman Filtering Applied to a Flexible-Joint Robot with Jerk Estimation

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Mohammad Ali Badamchizadeh ◽  
Iraj Hassanzadeh ◽  
Mehdi Abedinpour Fallah
Keyword(s):  
Initial Conditions ◽  
Covariance Matrices ◽  
Flexible Joints ◽  
Velocity Measurements ◽  
Lagrange Equations ◽  
Robust Nonlinear Control ◽  
Flexible Joint ◽  
Flexible Joint Robots ◽  
Simulation Results

Robust nonlinear control of flexible-joint robots requires that the link position, velocity, acceleration, and jerk be available. In this paper, we derive the dynamic model of a nonlinear flexible-joint robot based on the governing Euler-Lagrange equations and propose extended and unscented Kalman filters to estimate the link acceleration and jerk from position and velocity measurements. Both observers are designed for the same model and run with the same covariance matrices under the same initial conditions. A five-bar linkage robot with revolute flexible joints is considered as a case study. Simulation results verify the effectiveness of the proposed filters.

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