Salah Al-Sharhan,
Fakhri Karray,
and Wail Gueaieb.
Learning-Based Resource Optimization in Asynchronous Transfer Mode (ATM) Networks.
IEEE Transactions on Systems, Man and Cybernetics, Part B,
33(1):122-132,
February 2003.
@article{AlKaGu01,
author = "Salah Al-Sharhan and Fakhri Karray and Wail Gueaieb",
title = "Learning-Based Resource Optimization in Asynchronous Transfer Mode {(ATM)} Networks",
Journal = "IEEE Transactions on Systems, Man and Cybernetics, Part {B}",
year = "2003",
volume = "33",
number = "1",
pages = "122--132",
month = "February",
url = {},
note = ""
}
Wail Gueaieb,
Fakhri Karray,
and Salah Al-Sharhan.
A Robust Adaptive Fuzzy Position/Force Control Scheme for Cooperative Manipulators.
IEEE Transactions on Control Systems Technology,
11(4):516-528,
July 2003.
Abstract: |
We examine in this article the complex problem of simultaneous position and internal force control in multiple cooperative manipulator systems. This is done in the presence of unwanted parametric and modeling uncertainties as well as external disturbances. A decentralized adaptive fuzzy controller scheme is proposed here. The controller makes use of a multi-input multi-output fuzzy logic engine and a systematic online adaptation mechanism. Unlike conventional adaptive controllers, the proposed algorithm does not require a precise mathematical model of the system's dynamics nor does it require a linear parameterization of the system's uncertain physical parameters. Using a Lyapunov stability approach, the controller is proven to be robust in the face of varying intensity levels of the aforementioned uncertainties. The position and the internal forces are also shown to asymptotically converge to zero under such conditions. The performance of the controller proposed is then compared with that of a well known conventional adaptive controller. |
@article{GuKaAl02,
author = "Wail Gueaieb and Fakhri Karray and Salah Al-Sharhan",
title = "A Robust Adaptive Fuzzy Position/Force Control Scheme for Cooperative Manipulators",
Journal = "IEEE Transactions on Control Systems Technology",
year = "2003",
volume = "11",
number = "4",
pages = "516--528",
month = "July",
url = {},
note = "",
abstract = {We examine in this article the complex problem of simultaneous position and internal force control in multiple cooperative manipulator systems. This is done in the presence of unwanted parametric and modeling uncertainties as well as external disturbances. A decentralized adaptive fuzzy controller scheme is proposed here. The controller makes use of a multi-input multi-output fuzzy logic engine and a systematic online adaptation mechanism. Unlike conventional adaptive controllers, the proposed algorithm does not require a precise mathematical model of the system's dynamics nor does it require a linear parameterization of the system's uncertain physical parameters. Using a Lyapunov stability approach, the controller is proven to be robust in the face of varying intensity levels of the aforementioned uncertainties. The position and the internal forces are also shown to asymptotically converge to zero under such conditions. The performance of the controller proposed is then compared with that of a well known conventional adaptive controller.}
}