1. Wail Gueaieb. Soft Computing Based Approaches for the Robust Control of Cooperative Manipulator Systems. PhD thesis, Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada, June 2001.
   

   @phdthesis{WailPhD01,
   author = "Wail Gueaieb",
   title = "Soft Computing Based Approaches for the Robust Control of Cooperative Manipulator Systems",
   school = "Department of Systems Design Engineering, University of Waterloo",
   year = "2001",
   address = "Waterloo, Ontario, Canada",
   month = "June",
   note = "",
   url = {},
   abstract = {} 
   }
   

1. Salah Al-Sharhan, Fakhri Karray, and Wail Gueaieb. An Approach of Optimizing Computer Networks Using Soft Computing Techniques. In Proceedings of the International Conference on Software, Telecommunications and Computer Networks (SOFTCOM'01), volume 2, Split, Dubrovnik (Croatia), Ancona, Bari (Italy), pages 847-854, October, 9--12 2001. Abstract:

   This paper tackles the issue of topology design problem in broadband integrated-services digital networks using recently developed soft computing techniques. The design of a high-speed backbone network aims at finding the topology configuration that satisfies the traffic requirements and performance and reliability constraints with minimal cost. The new multimedia application and the dynamic and rapidly changed environment of the backbone networks make the topology design a new challenge. The population-based incremental learning (PBIL), combines in an efficient way the features of genetic algorithms (GA) and competitive learning. In this work, the PBIL algorithm is proposed to handle the topology design problem in computer networks.

   
   

   @inproceedings{AlKaGu01b,
   author = "Salah Al-Sharhan and Fakhri Karray and Wail Gueaieb",
   title = "An Approach of Optimizing Computer Networks Using Soft Computing Techniques",
   booktitle = "Proceedings of the International Conference on Software, Telecommunications and Computer Networks (SOFTCOM'01)",
   year = "2001",
   volume = 2,
   pages = "847--854",
   address = "Split, Dubrovnik (Croatia), Ancona, Bari (Italy)",
   month = "October, 9--12",
   editor = "",
   publisher = "",
   organization = "",
   url = {},
   abstract = {This paper tackles the issue of topology design problem in broadband integrated-services digital networks using recently developed soft computing techniques. The design of a high-speed backbone network aims at finding the topology configuration that satisfies the traffic requirements and performance and reliability constraints with minimal cost. The new multimedia application and the dynamic and rapidly changed environment of the backbone networks make the topology design a new challenge. The population-based incremental learning (PBIL), combines in an efficient way the features of genetic algorithms (GA) and competitive learning. In this work, the PBIL algorithm is proposed to handle the topology design problem in computer networks.} 
   }
   




2. Salah Al-Sharhan, Fakhri Karray, and Wail Gueaieb. Tools of computational intelligence as applied to bandwidth allocation in ATM networks. In Proceedings of the IEEE International Conference on Communications, Helsinki, Finland, pages 2907-2913, June 11--14 2001. Abstract:

   This paper presents the application of soft computing-based techniques to the bandwidth allocation (BA) problem in ATM networks. Efficient bandwidth allocation technique implies effective resources utilization. The fluid flow model has been known to be among the most accurate conventional methods to estimate the bandwidth of a set of connections. However, and due to the computational complexity, such methods have been proven to be inefficient in coping with varying and conflicting bandwidth requirements in ATM networks. To overcome this difficulty, many approximation-based solutions were introduced. Although such solutions are not simple, they nevertheless suffer from possible inaccuracy in estimating the required bandwidth. Soft computing-based bandwidth controllers, such as neural networks and neurofuzzy based controllers, have the capability to solve indeterminate non-linear input-output relations by learning from examples. Applying these techniques to the bandwidth allocation problem in ATM network yields a flexible control mechanism that offers a fundamental trade-off for the accuracy-simplicity dilemma.

   
   

   @inproceedings{AlKaGu01a,
   author = "Salah Al-Sharhan and Fakhri Karray and Wail Gueaieb",
   title = "Tools of computational intelligence as applied to bandwidth allocation in {ATM} networks",
   booktitle = "Proceedings of the IEEE International Conference on Communications",
   year = "2001",
   pages = "2907--2913",
   address = "Helsinki, Finland",
   month = "June 11--14",
   editor = "",
   publisher = "",
   organization = "",
   url = {},
   abstract = {This paper presents the application of soft computing-based techniques to the bandwidth allocation (BA) problem in ATM networks. Efficient bandwidth allocation technique implies effective resources utilization. The fluid flow model has been known to be among the most accurate conventional methods to estimate the bandwidth of a set of connections. However, and due to the computational complexity, such methods have been proven to be inefficient in coping with varying and conflicting bandwidth requirements in ATM networks. To overcome this difficulty, many approximation-based solutions were introduced. Although such solutions are not simple, they nevertheless suffer from possible inaccuracy in estimating the required bandwidth. Soft computing-based bandwidth controllers, such as neural networks and neurofuzzy based controllers, have the capability to solve indeterminate non-linear input-output relations by learning from examples. Applying these techniques to the bandwidth allocation problem in ATM network yields a flexible control mechanism that offers a fundamental trade-off for the accuracy-simplicity dilemma.} 
   }
   




3. Salah Al-Sharhan, Fakhri Karray, Wail Gueaieb, and O. Basir. Fuzzy Entropy: a Survey. In Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'01), Melbourne, Australia, pages 1135-1139, December 2--5 2001.
   

   @inproceedings{AlKaGu01c,
   author = "Salah Al-Sharhan and Fakhri Karray and Wail Gueaieb and O. Basir",
   title = "Fuzzy Entropy: a Survey",
   booktitle = "Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'01)",
   year = "2001",
   pages = "1135--1139",
   address = "Melbourne, Australia",
   month = "December 2--5",
   editor = "",
   publisher = "",
   organization = "",
   url = {},
   abstract = {} 
   }
   




4. Salah Al-Sharhan, Fakhri Karray, Wail Gueaieb, and Otman Basir. Resource Allocation in ATM Networks: A Fuzzy Logic Approach. In Proceedings of the Tunisian-German Conference on Smart Systems and Devices, Hammamet, Tunisia, pages 421-426, March 27--30 2001. Abstract:

   This paper presents the application of fuzzy logic-based techniques to ATM networks resource allocation, e.g., bandwidth allocation (BA) problem. Efficient bandwidth allocation technique implies effective resources utilization. Fluid flow model has been known to be among the most accurate conventional methods to estimate the bandwidth of a set of connections. However, and due to the computational complexity, such methods have been proven to be inefficient in coping with varying and conflicting bandwidth requirements in ATM networks. To overcome this difficulty, many approximation-based solutions were introduced. Although such solutions are not complicated, they nevertheless suffer from possible inaccuracy in estimating the required bandwidth. Soft computing-based bandwidth controllers, such fuzzy logic controllers, have the capability to approximate the non-linear input-output relations by means of linguistic variables and inference rules. Applying these techniques to the bandwidth allocation problem in ATM network yields a flexible control mechanism that offers a fundamental trade-off for the accuracy-simplicity dilemma.

   
   

   @inproceedings{AlKaGuBa01,
   author = "Salah Al-Sharhan and Fakhri Karray and Wail Gueaieb and Otman Basir",
   title = "Resource Allocation in {ATM} Networks: A Fuzzy Logic Approach",
   booktitle = "Proceedings of the Tunisian-German Conference on Smart Systems and Devices",
   year = "2001",
   pages = "421--426",
   address = "Hammamet, Tunisia",
   month = "March 27--30",
   editor = "",
   publisher = "",
   organization = "",
   url = {},
   abstract = {This paper presents the application of fuzzy logic-based techniques to ATM networks resource allocation, e.g., bandwidth allocation (BA) problem. Efficient bandwidth allocation technique implies effective resources utilization. Fluid flow model has been known to be among the most accurate conventional methods to estimate the bandwidth of a set of connections. However, and due to the computational complexity, such methods have been proven to be inefficient in coping with varying and conflicting bandwidth requirements in ATM networks. To overcome this difficulty, many approximation-based solutions were introduced. Although such solutions are not complicated, they nevertheless suffer from possible inaccuracy in estimating the required bandwidth. Soft computing-based bandwidth controllers, such fuzzy logic controllers, have the capability to approximate the non-linear input-output relations by means of linguistic variables and inference rules. Applying these techniques to the bandwidth allocation problem in ATM network yields a flexible control mechanism that offers a fundamental trade-off for the accuracy-simplicity dilemma.} 
   }
   




5. Wail Gueaieb, Fakhri Karray, and Salah Al-Sharhan. An Adaptive Fuzzy Control Approach for Cooperative Manipulators. In Proceedings of the International Symposium on Intelligent Control (ISIC'01), Mexico City, Mexico, pages 167-172, September 5--7 2001. 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. The performance of the controller proposed is then compared to that of a well known conventional adaptive controller.

   
   

   @inproceedings{GuKaAl01,
   author = "Wail Gueaieb and Fakhri Karray and Salah Al-Sharhan",
   title = "An Adaptive Fuzzy Control Approach for Cooperative Manipulators",
   booktitle = "Proceedings of the International Symposium on Intelligent Control (ISIC'01)",
   year = "2001",
   pages = "167--172",
   month = "September 5--7",
   address = "Mexico City, Mexico",
   editor = "",
   publisher = "",
   organization = "",
   url = {},
   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. The performance of the controller proposed is then compared to that of a well known conventional adaptive controller.} 
   }
   

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