Add to ORKGThis paper presents a new acceleration feedback controller for a five-bar parallel manipulator without acceleration sensors. The acceleration signals are estimated based on the closed-loop constraint equation of the kinematic chains in the parallel manipulator. The acceleration feedback control law is designed by using the high-gains, and the stability of the closed-loop control system is proved by the Lyapunov method. The advantages of the acceleration feedback controller are validated on a five-bar parallel manipulator platform, and the experimental results are compared with the PD controller without acceleration feedback loop. © 2012 Chinese Assoc of Automati
Traditional manipulator is based on serial design that has the advantages of large workspace and sim...
Trajectory tracking control of parallel manipulators is aimed in the presence of flexibility at the ...
Angular acceleration estimation and its application in acceleration feedback control are investigate...
The control law that is investigated in this thesis is referred to as the acceleration feedback cont...
In this study, classical PD control for direct drive motor system is enhanced to suppress disturbing...
This paper investigates dynamic simulation and trajectory tracking control of hybrid‐driven pl...
Independent joint control for robots is enhanced to suppress the dynamic couplings by incorporating ...
Parallel manipulators are characterized as having closed-loop kinematic chains. Compared to serial m...
With the increasing requirements on speed and accuracy in current day manipulators, flexibility effe...
International audienceThis paper presents a comparison between control/state estimation methods appl...
The dynamic model of a robot manipulator is described by a set of nonlinear, highly coupled differen...
International audienceTo ensure optimal performance of parallel robots, a rigorous design process ha...
Based on the dynamic model, a novel non-linear tracking controller is developed to overcome the nonl...
© IMechE 2017. In this study, a new terminal converging adaptive control approach with bounded contr...
This paper introduces a family of statically balanced five-degree-of-freedom (5DOF) parallel mechani...
Traditional manipulator is based on serial design that has the advantages of large workspace and sim...
Trajectory tracking control of parallel manipulators is aimed in the presence of flexibility at the ...
Angular acceleration estimation and its application in acceleration feedback control are investigate...
The control law that is investigated in this thesis is referred to as the acceleration feedback cont...
In this study, classical PD control for direct drive motor system is enhanced to suppress disturbing...
This paper investigates dynamic simulation and trajectory tracking control of hybrid‐driven pl...
Independent joint control for robots is enhanced to suppress the dynamic couplings by incorporating ...
Parallel manipulators are characterized as having closed-loop kinematic chains. Compared to serial m...
With the increasing requirements on speed and accuracy in current day manipulators, flexibility effe...
International audienceThis paper presents a comparison between control/state estimation methods appl...
The dynamic model of a robot manipulator is described by a set of nonlinear, highly coupled differen...
International audienceTo ensure optimal performance of parallel robots, a rigorous design process ha...
Based on the dynamic model, a novel non-linear tracking controller is developed to overcome the nonl...
© IMechE 2017. In this study, a new terminal converging adaptive control approach with bounded contr...
This paper introduces a family of statically balanced five-degree-of-freedom (5DOF) parallel mechani...
Traditional manipulator is based on serial design that has the advantages of large workspace and sim...
Trajectory tracking control of parallel manipulators is aimed in the presence of flexibility at the ...
Angular acceleration estimation and its application in acceleration feedback control are investigate...