Mohamed F. Khelfi

Work place: University of Oran, Faculty of Exact and Applied Sciences, RIIR Lab, Oran, 31000, Algeria



Research Interests: Robotics, Computer Architecture and Organization, Computing Platform, Process Control System, Data Structures and Algorithms


Mohamed. F. Khelfi was born in Algiers, Algeria. He received Ph.D. degree in Automatic Control from Nancy University, France, in 1995.  He is currently Professor at the Computer Science Department - Faculty of Sciences Exact and Applied Sciences - University of Oran - Algeria. He is also a research member at the Laboratory of Research in Industrial Computing and Networks. His main research interests include Automatic Control, Industrial Computing, Robotics and Networks.

Author Articles
Predator and Prey Modified Biogeography Based Optimization Approach (PMBBO) in Tuning a PID Controller for Nonlinear Systems

By Mohammed Salem Mohamed F. Khelfi

DOI:, Pub. Date: 8 Oct. 2014

In this paper an enhanced approach based on a modified biogeography optimization with predator and prey behavior (PMBBO) is presented. The approach uses several predators with new proposed prey’s movement formula. The potential of using a modified predator and prey model is to increase the diversification along the optimization process so to avoid local optima and reach the optimal solution quickly. The proposed approach is used in tuning the gains of PID controller for nonlinear systems (Mass spring damper and an inverted pendulum) and has given remarkable results when compared to genetic algorithm and classical BBO.

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Sequential Adaptive RBF-Fuzzy Variable Structure Control Applied to Robotics Systems

By Mohammed Salem Mohamed F. Khelfi

DOI:, Pub. Date: 8 Aug. 2014

In this paper, we present a combination of sequential trained radial basis function networks and fuzzy techniques to enhance the variable structure controllers dedicated to robotics systems. In this aim, four RBFs networks were used to estimate the model based part parameters (Inertia, Centrifugal and Coriolis, Gravity and Friction matrices) of a variable structure controller so to respond to model variation and disturbances, a sequential online training algorithm based on Growing-Pruning "GAP" strategy and Kalman filter was implemented. To eliminate the chattering effect, the corrective control of the VS control was computed by a fuzzy controller. Simulations are carried out to control three degrees of freedom SCARA robot manipulator where the obtained results show good disturbance rejection and chattering elimination.

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