On estimation of dynamic friction

Friedland, Bernard; Mentzelopoulou, Sophia E.

doi:10.1109/cdc.1993.325528

Cited by 17 publications

(7 citation statements)

References 11 publications

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“…To compensate for friction variations, methods have been proposed for online estimation of friction parameters using adaptive and observer-based approaches [2,5,12,17]. These methods take advantage of known and measured system dynamics to identify the friction parameters online.…”

Section: B Background Literaturementioning

confidence: 99%

“…A full listing of the identified and calculated parameters this system, as well as further details of this stability analysis are found in[4].Once the parameters of the system have been identified, the transfer function between applied user force and applied force of the manipulator on the environment may be calculated as a function of the admittance law. The closed loop position controller transfer function is shown in(12)…”

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confidence: 99%

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A control architecture for a mobile heavy-lift precision manipulator with limited sensory information

et al. 2007

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SUMMARYMobile robotic manipulators can augment the strength and dexterity of human operators in unstructured environments. Here, the control system for a six degree-of-freedom heavy-lift mobile manipulator for lifting and inserting payloads on the deck of a ship is described. The robotic hardware and the application present several control challenges, including structural resonances, high joint friction that varies with time, limited sensors for measuring the joint friction, complex interaction with the environment, tight tolerances for the insertion tasks, lack of bilateral force feedback of the contact forces, and ship motions. The control system enables an operator to perform insertion tasks using feedback of tactile clues of the manipulator position, and reduces the effects of friction with a combination of sensor-based, adaptive, and model-based methods of friction compensation. The control architecture is validated in simulation and on a laboratory manipulator.

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Section: B Background Literaturementioning

confidence: 99%

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confidence: 99%

A control architecture for a mobile heavy-lift precision manipulator with limited sensory information

et al. 2007

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“…These methods are being polished in time but maintain the same theoretical core [312]. Practical applications of these methods can be found in [313]. More sophisticated applications of the same methods are demonstrated [267], A host of experimental data is demonstrated in [314],…”

Section: Sensor Fusionmentioning

confidence: 99%

Intelligent systems:

Meystel¹

2002

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“…Many works were done in this field. For example, Coulomb friction model was done [9], [10], and since Coulomb friction represent only a part of friction behavior, other works were done for more complicated friction model like Coulomb and viscous friction [11] and the coulomb and viscous friction with Stribeck effect [12]- [14]. Identification of the GMS model is not yet well investigated.…”

Section: Introductionmentioning

confidence: 99%

Filtering approaches for online identification of GMS friction model

Grami

Aissaoui

2011

2011 IEEE EUROCON - International Conference on Computer as a Tool

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This paper deals with an online identification of the Generalized Maxwell Slip (GMS) friction model for both presliding and sliding regime at the same time. This identification is based on robust adaptive observer without friction force measurement. To apply the observer, a new approach of calculating the filtered friction force from the measurable signals is introduced. Moreover, two approximations are proposed to get the friction model linear over the unknown parameters and an approach of suitable filtering is introduced to guarantee the continuity of the model. Simulation results are presented to prove the efficiency of the approach of identification.

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On estimation of dynamic friction

Cited by 17 publications

References 11 publications

A control architecture for a mobile heavy-lift precision manipulator with limited sensory information

A control architecture for a mobile heavy-lift precision manipulator with limited sensory information

Intelligent systems:

Filtering approaches for online identification of GMS friction model

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