@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}
}
