@conference {435,
	title = {Distributed Cooperative LFC Protocols for Regulation Synchronization for Networked Multi-area Power Grid Networks},
	booktitle = {47th Annual Conference of the IEEE Industrial Electronics Society (IES)},
	year = {2021},
	month = {10/2021},
	author = {Shafiqul  Islam},
	editor = {Jorge Dias and Anderson Sunda-Meya}
}
@proceedings {428,
	title = {Robust Adaptive Finite-Time Consensus Tracking Protocols for a Group of Nonlinear Autonomous Systems},
	year = {2019},
	month = {11/2019},
	publisher = {IEEE},
	address = {Italy},
	doi = {10.1109/SMC.2019.8914028},
	author = {S. Islam}
}
@proceedings {426,
	title = {Robust Adaptive Tracking Synchronization Protocols for Leader-Follower Multirotor Aerial Vehicles with Uncertainty},
	year = {2019},
	month = {11/2019},
	publisher = {IEEE},
	address = {Italy},
	abstract = { This   paper  develops  robust   adaptive  tracking synchronization protocol for a group of cloud connected leader-follower  multirotor  aerial  vehicles  (MAVs)  with  uncertainty. The design combines adaptive learning mechanism with sliding mode control vectors to solve consensus tracking synchroniza-tion  problem  for  both  attitude  and  position  dynamics.  The protocols are constructed by using local and neighboring states of  the  vehicles  provided  that  the  vehicles  can  share  states information with  neighboring vehicles via local area network. Adaptive learning algorithms are used locally for each vehicle to  deal  with  uncertainty  associated  with  nonlinear  dynamics and uncertain flying environment. Lyapunov and sliding mode control method is employed to design and analyze asymptotic convergence  of  the  consensus  tracking  error  functions.  The convergence  analysis  shows  that  the  states  of  the  follower vehicles can reach an agreement and synchronize to the leader vehicle achieving  ensuring tracking synchronization property. The  protocols  design  and  implementation  is  simple  as  they do  not  require  exact  knowledge of  the  dynamical  model  and uncertainty. 

},
	doi = {10.1109/SMC.2019.8914373},
	author = {Shafiqul Islam and Abdulmotaleb El Saddik and Anderson Sunda-Meya}
}
@article {425,
	title = {Robust Asymptotic and Finite-time Tracking for Second-order Nonlinear Multi-agent Autonomous Systems},
	journal = {International Journal of Control Automation and Systems},
	volume = {17},
	year = {2019},
	month = {12/2019},
	type = {Research },
	chapter = {3069},
	abstract = {This paper investigates consensus based distributed robust asymptotic and finite-time tracking control strategy for second-order multi-agent autonomous systems. The protocol design uses states of the neighboring agents with directed communication topology in the presence of uncertainty associated with the autonomous agents. Robust adaptive learning algorithm uses with the protocol design for each follower agent to learn and adapt bounded uncertainty associated with nonlinear dynamics of the follower agents. Adaptive learning protocol also integrates with the follower agents protocol to learn and adapt bounded input of the leader. Lyapunov method with Graph, classical sliding mode, and terminal sliding mode theory use to guarantee that the proposed distributed control design can reach an agreement and follow the states of the leader in both finite-time and asymptotic sense. Analysis shows that consensus based protocol can force the states of the followers sliding surface to track the states of the leader sliding surface in finite-time and remain there. The proposed distributed consensus protocol does not require the exact bound of the uncertainty associated with the follower agents. Also, the proposed protocol does not require the exact bound of the leader input as opposed to other distributed cooperative control designs. Evaluation results with comparison are presented to demonstrate the validity of the theoretical argument for the real-time applications.},
	author = {Shafiqul Islam and Nicolas Xiros}
}
@proceedings {427,
	title = {Robust Cooperative Load-Frequency Tracking Protocols for Leader-Follower Smart Power Grid Networks With Uncertainty},
	year = {2019},
	month = {11/2019},
	publisher = {IEEE},
	address = {Italy},
	doi = {10.1109/SMC.2019.8914446},
	author = {Shafiqul Islam and Abdulmotaleb El Saddik}
}
@proceedings {430,
	title = {Consensus Based Distributed Cooperative Control for Multiple Miniature Aerial Vehicles with Uncertainty},
	year = {2018},
	month = {11/2018},
	doi = {10.1109/SMC.2017.8122995},
	author = {Shafiqul Islam},
	editor = {Peter Liu and A. El Saddik}
}
@proceedings {429,
	title = {Consensus Based Distributed Robust Adaptive Control for Second-Order Nonlinear Multi-agent Systems with Uncertainty},
	year = {2018},
	month = {11/2018},
	doi = {10.1109/SMC.2018.00451},
	author = {Shafiqul Islam},
	editor = {Toufik Khawl and Abdelaziz Saeed Mohamed Alzaabi and Anderson Sunda-Meya}
}
@conference {418,
	title = {A Search-Based Approach to Solve Pursuit-Evasion Games with Limited Visibility in Polygonal Environments},
	booktitle = {International Conference on Autonomous \& Multiagent Systems (AAMAS)},
	year = {2018},
	url = {http://dl.acm.org/citation.cfm?id=3237383.323795},
	author = {Quattrini Li, Alberto and Raffaele Fioratto and Francesco Amigoni and Volkan Isler}
}
@proceedings {431,
	title = {Consensus Based Distributed Cooperative Control for Multiple Miniature Aerial Vehicles with Uncertainty},
	year = {2017},
	month = {11/2017},
	publisher = {IEEE},
	doi = {10.1109/SMC.2017.8122995},
	author = {Shafiqul Islam},
	editor = {P. X. Liu and A. El Saddik}
}
@proceedings {432,
	title = {Distributed Robust Adaptive Finite-Time Voltage Control for AC Microgrids with Uncertainty},
	year = {2017},
	month = {11/2017},
	doi = {10.1109/SMC.2017.8122946},
	author = {S. Islam},
	editor = {P. X. Liu and A. El  Saddik}
}
@proceedings {434,
	title = {Distributed Robust Adaptive Finite-Time Voltage Control for AC Microgrids with Uncertainty},
	year = {2017},
	month = {11/2017},
	doi = {10.1109/SMC.2017.8122946},
	author = {Shafiqul Islam},
	editor = {Peter Liu and Abdulmotaleb El Saddik}
}
@conference {144,
	title = {Multi-Target Visual Tracking with UAVs},
	booktitle = {2014 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems},
	year = {2014},
	month = {09/2014},
	address = {Chicago, IL},
	abstract = {We study the problem of tracking mobile targets using a team of aerial robots. Each robot carries a camera to detect targets moving on the ground. The overall goal is to plan for the trajectories of the robots in order to track the most number of targets, and accurately estimate the target locations using the images. The two objectives can conflict since a robot may fly to a higher altitude and potentially cover a larger number of targets at the expense of accuracy. We start by showing that k >= 3 robots may not be able to track all n targets while maintaining a constant factor approximation of the optimal quality of tracking at all times. Next, we study the problem of choosing robot trajectories to maximize either the number of targets tracked or the quality of tracking. We formulate this problem as the weighted version of a combinatorial optimization problem known as the Maximum Group Coverage (MGC) problem. A greedy algorithm yields a 1/2 approximation for the weighted MGC problem. Finally, we evaluate the algorithm and the sensing model through simulations and preliminary experiments.},
	author = {Pratap Tokekar and Volkan Isler and Antonio Franchi}
}
@article {40,
	title = {RoboCup Rescue Robot and Simulation Leagues},
	journal = {AI Magazine},
	volume = {34},
	year = {2013},
	pages = {78{\textendash}87},
	abstract = {The RoboCup Rescue Robot and Simulation competitions have been held since 2000. The experience gained during these competitions has increased the maturity level of the field, which allowed deploying robots after real disasters (e.g. Fukushima Daiichi nuclear disaster). This article provides an overview of these competitions and highlights the state of the art and the lessons learned.},
	author = {H. L. Akin and N. Ito and A. Jacoff and A. Kleiner and J. Pellenz and A. Visser}
}
@inbook {217,
	title = {Computational Science and Its Applications - ICCSA 2011: International Conference, Santander, Spain, June 20-23, 2011. Proceedings, Part III},
	year = {2011},
	pages = {58{\textendash}73},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	chapter = {Multi-robot Visual Coverage Path Planning: Geometrical Metamorphosis of the Workspace through Raster Graphics Based Approaches},
	address = {Berlin, Heidelberg},
	isbn = {978-3-642-21931-3},
	doi = {10.1007/978-3-642-21931-3_5},
	url = {http://dx.doi.org/10.1007/978-3-642-21931-3_5},
	author = {Valente, Jo{\~a}o and Barrientos, Antonio and Del Cerro, Jaime and Rossi, Claudio and Colorado, Julian and Sanz, David and Garz{\'o}n, Mario},
	editor = {Murgante, Beniamino and Gervasi, Osvaldo and Iglesias, Andr{\'e}s and Taniar, David and Apduhan, Bernady O.}
}
