Wail Gueaieb,
Fakhri Karray,
and Salah Al-Sharhan.
Computational Intelligence Based Approach for the Joint Trajectory Generation of Cooperative Robotic Systems.
Journal of Systems Analysis Modelling Simulation,
42(10):1499-1520,
2002.
[WWW]
Abstract: |
We discuss here the implementation aspects of recently developed tools of computational intelligence as applied to joint trajectory generation of a class of multi-joint cooperative robotic systems. This is an issue closely related to the inverse kinematics problem which usually represents a heavy computational burden on the processing power of any complex robotic structure. High nonlinearities, heavy coupling between the degrees of freedom, and time variant configuration of the robot structure heavily contribute to these difficulties. Soft computing techniques have surged in recent years as effective computational tools for emulating the human capabilities when dealing with complex systems. Some of them are used here to synthesize approaches capable of substantially improving the solving of the inverse kinematics problem for a class of robotic systems and help in generating the joint trajectories in a faster way. Comparative results are provided in terms of accuracy and CPU time required for the execution of different trajectories. |
@article{GuKaAl02-c,
author = "Wail Gueaieb and Fakhri Karray and Salah Al-Sharhan",
title = "Computational Intelligence Based Approach for the Joint Trajectory Generation of Cooperative Robotic Systems",
Journal = "Journal of Systems Analysis Modelling Simulation",
year = "2002",
volume = 42,
number = 10,
pages = "1499--1520",
month = "",
publisher = "Taylor \& Francis",
url = {http://taylorandfrancis.metapress.com/app/home/contribution.asp?wasp=lp3ef1xgmh5ywnrhwbq6&referrer=parent&backto=searcharticlesresults,1,1;journal,1,1;linkingpublicationresults,id:104286,1},
note = "",
abstract = {We discuss here the implementation aspects of recently developed tools of computational intelligence as applied to joint trajectory generation of a class of multi-joint cooperative robotic systems. This is an issue closely related to the inverse kinematics problem which usually represents a heavy computational burden on the processing power of any complex robotic structure. High nonlinearities, heavy coupling between the degrees of freedom, and time variant configuration of the robot structure heavily contribute to these difficulties. Soft computing techniques have surged in recent years as effective computational tools for emulating the human capabilities when dealing with complex systems. Some of them are used here to synthesize approaches capable of substantially improving the solving of the inverse kinematics problem for a class of robotic systems and help in generating the joint trajectories in a faster way. Comparative results are provided in terms of accuracy and CPU time required for the execution of different trajectories.}
}
Fakhri Karray,
Wail Gueaieb,
and Salah Al-Sharhan.
The Hierarchical Expert Tuning of PID Controllers Using Tools of Soft Computing.
IEEE Transactions on Systems, Man and Cybernetics,
32(1):77-90,
February 2002.
Abstract: |
We present in this study soft computing based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing based controllers proposed are hybrid in nature in that, they integrate within a well defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed have also the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes. |
@article{KaGuAl01,
author = "Fakhri Karray and Wail Gueaieb and Salah Al-Sharhan",
title = "The Hierarchical Expert Tuning of {PID} Controllers Using Tools of Soft Computing",
Journal = "IEEE Transactions on Systems, Man and Cybernetics",
year = "2002",
volume = 32,
number = 1,
pages = "77--90",
month = "February",
url = {},
abstract = {We present in this study soft computing based results pertaining to the hierarchical tuning process of PID controllers located within the control loop of a class of nonlinear systems. The results are compared with PID controllers implemented either in a stand alone scheme or as a part of conventional gain scheduling structure. This work is motivated by the increasing need in the industry to design highly reliable and efficient controllers for dealing with regulation and tracking capabilities of complex processes characterized by nonlinearities and possibly time varying parameters. The soft computing based controllers proposed are hybrid in nature in that, they integrate within a well defined hierarchical structure the benefits of hard algorithmic controllers with those having supervisory capabilities. The controllers proposed have also the distinct features of learning and auto-tuning without the need for tedious and computationally extensive online systems identification schemes.}
}