Identification of joint stiffness with bandpass filtering

Pham, Minh Tu; Gautier, Maxime; Poignet, P.

doi:10.1109/robot.2001.933056

Cited by 50 publications

(35 citation statements)

References 9 publications

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“…The computation of joint velocities and accelerations is made by using the central difference algorithm in order to avoid any distortion of phase and amplitude. Practical aspects of the derivative calculation and data filtering are explained in [23].…”

Section: Data Filteringmentioning

confidence: 99%

A C5 parallel robot identification and control

Achili¹,

Daachi²,

Ali-Chérif³

et al. 2010

Int. J. Control Autom. Syst.

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The paper proposes a controller scheme based on a priori identification for a C5 parallel robot. First we realize the identification of dynamic parameters of the robot using the Least Squares technique. Different data are used for this step of identification. The cross validation permitted to select and confirm the identified parameters. After, a control scheme (computed torque) is applied to control the C5 parallel robot. The functions of this control scheme are based on precedent identified parameters. In order to reduce the effect of the identification error, we have added a robustness term based on sliding mode technique. The stability of the system in closed loop is presented using the Lyapunov principle. Experimental results of identification and control are presented and show the effectiveness of our methodology.

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Section: Data Filteringmentioning

confidence: 99%

A C5 parallel robot identification and control

Achili¹,

Daachi²,

Ali-Chérif³

et al. 2010

Int. J. Control Autom. Syst.

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show abstract

“…In this method, it is aimed to evaluate joint stiffness values of any 6R serial robot using the model based on the Conservative Congruence Transformation (CCT). (Pham et al;2001) proposed a method for identification of the joint stiffness values using band pass filtering. This method requires closed-loop control based on the robot's dynamic model.…”

Section: Introductionmentioning

confidence: 99%

Stiffness Analysis of Above Knee Prosthesis

Ege¹

2019

ijisae

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While a healthy human walks, his or her legs mutually perform good repeatability with high accuracy. This provides an esthetical movement and balance. People with above knee prosthesis want to perform walking as esthetical as a healthy human. Therefore, to achieve a healthy walking, the above knee prosthesis must provide a good stiffness performance. Especially stiffness values are required when adding a second axis movement to the ankle for eversion and inversion. In this paper, stiffness analysis of above-knee prosthesis is presented. The translational displacement of above knee prosthesis is obtained when the prosthesis is subjected to the external forces. Knowing stiffness values of the above knee prosthesis, designers can compute prosthesis parameters such as ergonomic structure, height, and weight and energy consumption.

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“…Indeed, when a load is applied to the robot end-effector, all deformations are considered including those due to the links deformations and/or radial joint stiffness values. Pham et al [18] proposed a method for the identification of joint stiffness with bandpass filtering and based on the robot's dynamic model. This method requires a closed-loop control in addition to real-time actuator currents.…”

Section: Introductionmentioning

confidence: 99%

Joint stiffness identification of industrial serial robots

Dumas

Caro

Chérif³

et al. 2011

Robotica

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This paper presents a new methodology for the joint stiffness identification of industrial serial robots and as consequence for the evaluation of both translational and rotational displacements of the robot's end-effector subject to an external wrench (force and torque). In this paper, the robot's links are supposed to be quite stiffer than the actuated joints as it is usually the case with industrial serial robots. The robustness of the identification method and the sensitivity of the results to measurement errors and number of experimental tests are also analyzed. The Kuka KR240-2 robot is used as an illustrative example throughout the paper.

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Identification of joint stiffness with bandpass filtering

Cited by 50 publications

References 9 publications

A C5 parallel robot identification and control

A C5 parallel robot identification and control

Stiffness Analysis of Above Knee Prosthesis

Joint stiffness identification of industrial serial robots

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