Virtual internal model following control of robot arms

Kosuge, Kazuhiro; Furuta, K.; Yokoyama, Tsugio

doi:10.1109/robot.1987.1087743

Cited by 48 publications

(10 citation statements)

References 9 publications

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“…A procedure to apply the virtual internal model (VIM) control [14] to the xy-stage is mentioned in this section. Any mechanical mechanism includes nonlinearity caused by friction, variances of viscosity, and unknown dynamics; hence, it is difficult to apply a linear system control theory to actual machine without any nonlinear compensation.…”

Section: Virtual Internal Model Control (Step 1)mentioning

confidence: 99%

Adaptive Impedance Control to Enhance Human Skill on a Haptic Interface System

Suzuki

Furuta

2012

Journal of Control Science and Engineering

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Adaptive assistive control for a haptic interface system is proposed in the present paper. The assistive control system consists of three subsystems: a servo controller to match the response of the controlled machine to the virtual model, an online identifier of the operator’s control characteristics, and a variable dynamics control using adaptive mechanism. The adaptive mechanism tunes an impedance of the virtual model for the haptic device according to the identified operator’s characteristics so as to enhance the operator’s control performance. The adaptive law is derived by utilizing a Lyapunov candidate function. Using a haptic interface device composed by axy-stage, an effectiveness of the proposed control method was evaluated experimentally. As a result, it was confirmed that the operator’s characteristics can be estimated sufficiently and that performance of the operation was enhanced by the variable dynamics assistive control.

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Section: Virtual Internal Model Control (Step 1)mentioning

confidence: 99%

Adaptive Impedance Control to Enhance Human Skill on a Haptic Interface System

Suzuki

Furuta

2012

Journal of Control Science and Engineering

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“…In order to suppress the inherent characteristics of mechanical components such as friction, non-linearities and variances of viscosity, the DD motors are controlled by local compensators designed using a virtual internal control method with impedance models [14]. The stage is controlled so that it behaves like a virtual model having specified properties of mass, stiffness and damping.…”

Section: Virtual Internal Model Controlmentioning

confidence: 99%

Assistance control on a haptic system for human adaptive mechatronics

Suzuki¹,

Kurihara²,

Furuta³

et al. 2006

Advanced Robotics

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Giving a natural operational feeling to a human via a haptic interface requires not only a sophisticated and intuitive mechanical design, but also an appropriate control system design. Most haptic systems, however, implicitly demand that the human gets used to manipulation of the haptic devices before he/she can get the feel of the virtual space and/or telepresence beyond the haptic device. Based on a new concept of a human-in-the-loop system called Human Adaptive Mechatronics (HAM), an assist-control for a force/vision interactive haptic system is discussed in this paper. The proposed assist-control scheme includes online estimation of a operator's control characteristics, and a 'force assist' function implemented as a change in the support ratio according to the identified skill level. We developed a HAM haptic device test system, performed evaluation experiments with this apparatus and analyzed the measured data. It was confirmed that the operator's skill could be estimated sufficiently and that operator's performance was enhanced by the assist-control.

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“…The robot "follows through" with the trajectory for 0.15 s after impact, then resets to an angle of 0.1 rad to await the next control. For feedback control of the arm along the trajectory, we use a type of virtual internal model following control (Kosuge et al [50]) to suppress unmodeled dynamics.…”

Section: Controlmentioning

confidence: 99%