@mastersthesis {65165,
	title = {Commande robuste appliqu{\'e}e {\`a} la navigation d\&$\#$39;un robot mobile},
	year = {2018},
	month = {2018},
	type = {Master{\textquoteright}s Thesis},
	author = {Ali, Mallem}
}
@article {64634,
	title = {Disturbances Elimination with Fuzzy Sliding Mode Control for Mobile Robot Trajectory Tracking, ISSN / e-ISSN 1336-1376 / 1804-3119},
	journal = {Advances in Electrical and Electronic EngineeringAdvances in Electrical and Electronic Engineering},
	volume = {Volume 16},
	year = {2018},
	month = {2018},
	pages = {pp 297-310},
	abstract = {The disturbances are the significant issue for the trajectory tracking of mobile robots. Therefore, an adequate control law is presented in this paper and this one is based on Global Terminal Sliding Mode (GTSM) with fuzzy control. This control law aims to guarantee the avoidance of the kinematic disturbances which are injected in the angular and linear velocities, respectively. Moreover, the dynamic model based on exponential reaching law is presented to avoid the uncertainties. The control law provides the asymptotic stability by taking into account the fuzzy rules and Lyapunov theory. Thus, the chattering phenomenon should be avoided. The simulation works prove the robustness of the proposed control law by considering the disturbances function and the robot can follow the desired trajectories.},
	author = {Walid, Benaziza and Noureddine, Slimane and Ali, Mallem}
}
@article {65162,
	title = {Robust control of mobile robot in presence of disturbances using neural network and global fast sliding mode, ISSN / e-ISSN 1064-1246 / 1875-8967},
	journal = {Journal of Intelligent And Fuzzy SystemsJournal of Intelligent And Fuzzy Systems},
	volume = {Volume 34},
	year = {2018},
	month = {2018},
	pages = {pp 4345-4354},
	abstract = {In this paper a dynamic tracking control of mobile robot using neural network global fast sliding mode (NN-GFSM) is presented. The proposed strategy combines two control approaches, kinematic control and dynamic control. The laws of kinematic control are based on GFSM in order to determine the adequate velocities for the system stability in finite time. The dynamic controller combines two control techniques, the GFSM to stabilize the velocities errors, and a neural network controller in order to approximate a nonlinear function and to deal the disturbances. This dynamic controller allows the robots to follow the desired trajectory even in the presence of disturbances. The designed controller is dynamically simulated by using Matlab/ Simulink and the simulations results show the efficiency and robustness of the proposed control strategy.},
	author = {Ali, Mallem and Noureddine, Slimane and Walid, Benaziza}
}
