Adaptive force control in robot manipulation with consideration of characteristics of objects. (1st report Grasping control of gripper by the adaptive hybrid force control)

敏男, 福田; 尚之, 北村; 和雄, 谷江

doi:10.1299/kikaic.53.726

Cited by 4 publications

(1 citation statement)

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“…Fukuda et al [35] presented a method of adaptive force control of a rigid manipulator taking the object's characteristics into consideration, and also proposed a feedback decoupling control for suppressing vibrations in position control of a flexible robot arm [36]. Then, Tokita and Fukuda [37] presented an adaptive force control of a robotic manipulator using neural networks.…”

Section: Torque Control Of a Flexible Beammentioning

confidence: 99%

Adaptive control and identification using one neural network for a class of plants with uncertainties

Tsuji

Kaneko

1998

IEEE Trans. Syst., Man, Cybern. A

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This paper proposes a new neural adaptive control method that can perform adaptive control and identification for a class of controlled plants with linear and nonlinear uncertainties. This method uses a single neural network for both control and identification, and a sufficient condition of the local asymptotic stability is derived. Then, in order to illustrate the applicability of the proposed method, it is applied to the torque control of a flexible beam that includes linear and nonlinear structural uncertainties.

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Section: Torque Control Of a Flexible Beammentioning

confidence: 99%

Adaptive control and identification using one neural network for a class of plants with uncertainties

Tsuji

Kaneko

1998

IEEE Trans. Syst., Man, Cybern. A

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Adaptive force control of direct drive motor for force sensor stiffness compensation

Fukuda

Arai

1991

Electrical Engineering Japan

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This paper deals with an adaptive control problem of direct drive (DD) robotic manipulators with force sensor stiffness. Since DD motor has advantages to force control in robotic application, so that many works have been reported so far in control problems. However, the dynamic compensation for the sensor stiffness has little been reported so far, even though the force sensor in DD robots decreases the stiffness of the overall DD robots. In order to make use of high stiffness of DD motors itself in the servo loop, it is necessary to take into account the sensor stiffness for the high gain dynamic control. Therefore, an adaptive dynamic compensation method is introduced here in the vein of the model reference adaptive control to widen the applicability of the DD robots, because the feedback with the constant gains may cause unstable behaviors, depending on objects dynamics. The applicability of the proposed method could be verified with some experiments. Then this method is applied to nonlinear objects, such as rotary channel. The experiments show the better performance by the proposed method for the nonlinear compensation than the conventional feedback control method. Thus, it is shown that the DD motor can have much wider applicabilities by the proposed adaptive force control.

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On a New Torque Sensor for Compliant Grasp by Robot Fingers with a Tendon Actuation System

Kaneko

Yokoi

Tanie

1989

Advanced Robotics: 1989

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Adaptive force control in robot manipulation with consideration of characteristics of objects. (1st report Grasping control of gripper by the adaptive hybrid force control)

Cited by 4 publications

References 1 publication

Adaptive control and identification using one neural network for a class of plants with uncertainties

Adaptive control and identification using one neural network for a class of plants with uncertainties

Adaptive force control of direct drive motor for force sensor stiffness compensation

On a New Torque Sensor for Compliant Grasp by Robot Fingers with a Tendon Actuation System

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