Global robust output feedback tracking control of robot manipulators

Robotica ◽  
2004 ◽  
Vol 22 (4) ◽  
pp. 351-357 ◽  
Author(s):  
W. E. Dixon ◽  
E. Zergeroglu ◽  
D. M. Dawson
Keyword(s):  
Output Feedback ◽  
Tracking Control ◽  
Robot Manipulators ◽  
Tracking Error ◽  
Parametric Uncertainty ◽  
Position Tracking ◽  
Incomplete Model ◽  
Bounded Disturbances ◽  
Position Tracking Control ◽  
Feedback Tracking

This paper addresses the problem of global output feedback, link position tracking control of robot manipulators. Specifically, a robust, Lyapunov-based controller is designed to ensure that the link position tracking error is globally uniformly ultimately bounded despite the fact that only link position measurements are available in the presence of incomplete model information (i.e., parametric uncertainty and additive bounded disturbances).

A composite adaptive output feedback tracking controller for robotic manipulators

Robotica ◽  
1999 ◽  
Vol 17 (6) ◽  
pp. 591-600 ◽  
Author(s):  
E. Zergeroglu ◽  
W. Dixon ◽  
D. Haste ◽  
D. Dawson
Keyword(s):  
Output Feedback ◽  
Tracking Control ◽  
Prediction Error ◽  
Tracking Error ◽  
Robotic Manipulators ◽  
Parameter Estimate ◽  
Position Tracking ◽  
Linear Filter ◽  
Velocity Measurements ◽  
Feedback Tracking

This paper provides a solution to the composite adaptive output feedback tracking control problem for robotic manipulators. The proposed controller utilizes an update law that is a composite of a gradient update law driven by the link position tracking error and a least squares update law driven by the prediction error. In order to remove the controller's dependence on link velocity measurements, a linear filter and a new prediction error formulation are designed. The controller provides semi-global asymptotic link position tracking performance. Experimental results illustrate that the proposed controller provides improved link position tracking error transient performance and faster parameter estimate convergence in comparsion to the same controller using a gradient update law.

scholarly journals Adaptive Output Feedback Tracking Controller Design of Stochastic Nonlinear Systems with Parameter Uncertainty for Polynomial Function Growth Conditions

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Long-Chuan Guo
Keyword(s):  
Nonlinear Systems ◽  
Output Feedback ◽  
Controller Design ◽  
Polynomial Function ◽  
Tracking Error ◽  
Parametric Uncertainty ◽  
Growth Conditions ◽  
Stochastic Nonlinear Systems ◽  
Tracking Controller ◽  
Feedback Tracking

This paper mainly focuses on output feedback practical tracking controller design for stochastic nonlinear systems with polynomial function growth conditions. Mostly, there are some studies on output feedback tracking control problem for general nonlinear systems with parametric certainty in existing achievements. Moreover, we extend it to stochastic nonlinear systems with parametric uncertainty and system nonlinear terms are assumed to satisfy polynomial function growth conditions which are more relaxed than linear growth conditions or power growth conditions. Due to the presence of unknown parametric uncertainty, an output feedback practical tracking controller with dynamically updated gains is constructed explicitly so that all the states of the closed-loop systems are globally bounded and the tracking error belongs to arbitrarily small interval after some positive finite time. An example illustrates the efficiency of the theoretical results.

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