The stability of the adapt tracking controller of rigid and flexible joint robots

1999 ◽  
Author(s):  
K. Kozlowski ◽  
P. Sauer
Keyword(s):  
Flexible Joint ◽  
Flexible Joint Robots ◽  
Tracking Controller ◽  
The Stability

An alternative stability proof for “Adaptive type-2 fuzzy estimation of uncertainties in the control of electrically flexible-joint robots”

2018 ◽  
Vol 25 (5) ◽  
pp. 977-983 ◽  
Author(s):  
Alireza Izadbakhsh ◽  
Payam Kheirkhahan
Keyword(s):  
Closed Loop ◽  
Loop System ◽  
Control Input ◽  
Closed Loop System ◽  
Flexible Joint ◽  
Flexible Joint Robots ◽  
Robust Stability Analysis ◽  
The Stability ◽  
Estimation Of Uncertainties

This short note points out an improvement on the robust stability analysis for electrically driven flexible joint robots (EDFJR) given in the 2017 paper by Zirkohi and Fateh, entitled “Adaptive type-2 fuzzy estimation of uncertainties in the control of electrically flexible-joint robots.” In their paper, the authors present an interval Type-2 Adaptive fuzzy control scheme for EDFJR. The nonlinearities associated with actuator input constraints have been also considered in their paper. They discussed the saturated and unsaturated region of the control input separately and neglected the transition state between these regions. Moreover, they did not guarantee the stability of the closed-loop system in the saturated area. In this note, an alternative stability proof is presented that does not require this separation, and which guarantees the stability in a more general framework. The overall closed-loop system is proven to be robust, and bounded-input, bounded-output stable, while the motor/joint position errors are uniformly-ultimately bounded based on the Lyapunov's stability concept.

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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