Robust model-based control: an experimental case study

Leahy, M.B.; Bossert, David E.; Whalen, Paul V.

doi:10.1109/robot.1990.126297

Cited by 34 publications

(4 citation statements)

References 13 publications

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“…In [24], the authors present data showing that given equal feedback gains the comparative performance of IDCFA control is superior to that of PDF control. This is corroborates previous experimental observations showing model-based controllers to provide performance superior to PD-type controllers over a wide range of operating conditions [14], [25], [27].…”

Section: B Force Controller Performancesupporting

confidence: 91%

“…2) IDCF-Model-Based Force Control: This model-based controller is defined in 7of Section II-B and will be denoted IDCF. Adopting the commonly used notation for robot dynamics in which a vector, , of known plant parameters is explicitly factored out, e.g., [1], the equation of robot motion (1) can be written (12) Using this notation, the controller (7) can be written (13) (14) where and are defined in Section II-B.…”

Section: A Three Force Control Algorithmsmentioning

confidence: 99%

“…1) The Effect of Model-Based Rigid-Body Feedforward: Given the diversity of experimental results for model-based control of unconstrained robot motion, e.g., [1], [8], [14], [23], [25], [27], in the present context of force control it seems essential to investigate the comparative performance of model-based versus nonmodel-based force controllers. The purpose of this section is to compare the performance of the nonmodel-based PDF controller (11) with the fully adaptive model-based IDCFA controller (15).…”

Section: B Force Controller Performancementioning

confidence: 99%

See 2 more Smart Citations

Adaptive model-based hybrid control of geometrically constrained robot arms

Whitcomb

Arimoto

Naniwa

et al. 1997

IEEE Trans. Robot. Automat.

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This paper reports comparative experiments with a new model-based adaptive force control algorithm for robot arms. This controller provides simultaneous position and force trajectory tracking of a robot arm whose tool tip is in point contact with a smooth rigid surface. The algorithm is provably stable with respect to the commonly accepted rigid-body nonlinear dynamical model for robot arms. Comparative experiments show the new adaptive model-based controller to provide performance superior to that of both nonmodel-based controllers and nonadaptive controllers over a wide range of operating conditions.

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Section: B Force Controller Performancesupporting

confidence: 91%

Section: A Three Force Control Algorithmsmentioning

confidence: 99%

Section: B Force Controller Performancementioning

confidence: 99%

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Adaptive model-based hybrid control of geometrically constrained robot arms

Whitcomb

Arimoto

Naniwa

et al. 1997

IEEE Trans. Robot. Automat.

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“…Wang and Gao [5] have reported inverse dynamics model-based control for flexible-link robots, based on modal analysis, i.e., on the assumption that the deformation of the flexible-link can be written as a finite series expansion containing the elementary vibration modes. Leahy et al [6] worked on robust model based control. They also discussed an experimental case.…”

Section: Introductionmentioning

confidence: 99%

Reduced Model Based Control of Two Link Flexible Space Robot

Kumar¹,

Pathak²,

Sukavanam³

2011

ICA

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Model based control schemes use the inverse dynamics of the robot arm to produce the main torque component necessary for trajectory tracking. For model-based controller one is required to know the model parameters accurately. This is a very difficult task especially if the manipulator is flexible. So a reduced model based controller has been developed, which requires only the information of space robot base velocity and link parameters. The flexible link is modeled as Euler Bernoulli beam. To simplify the analysis we have considered Jacobian of rigid manipulator. Bond graph modeling is used to model the dynamics of the system and to devise the control strategy. The scheme has been verified using simulation for two links flexible space manipulator

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Feedback control of robot Arm with discrete nonlinear model

1992

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This article looks at the problem of controlling a robot arm from a discrete time perspective. We develop the theories and obtain results that feedback linearizes the discrete nonlinear system representing a PUMA 560 robot arm. The effect of sampling on the performance of the arm has been studied and shown through experiments. The results presented here, where the nonlinear robot model has been linearized and controlled completely in discrete time, are new to the robotics literature. We shown certain restrictions necessary on the sampling time of the system. The results obtained have been experimentally verified at the Center for Robotics and Automation at Washington University. Because a number of researchers have addressed the problem of loss of feedback linearizability under sampling, it was important to develop theories and obtain results in discrete time that take into consideration the effects due to sampling. This problem has been addressed here. Analysis of the control law under the assumptions of bounded input is performed and a recursive sensitivity function is derived. The results we obtain in discrete time show the dependency of the performance of the arm on the sampling time. It has been seen that with a higher sampling frequency the performance of the arm substantially improves and it is expected that close to lo00 Hz sampling rate, the peak performance of the PUMA 560 robot arm, will be reached.

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Robust model-based control: an experimental case study

Cited by 34 publications

References 13 publications

Adaptive model-based hybrid control of geometrically constrained robot arms

Adaptive model-based hybrid control of geometrically constrained robot arms

Reduced Model Based Control of Two Link Flexible Space Robot

Feedback control of robot Arm with discrete nonlinear model

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