Mohamed Tarbouchi

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The development of autonomous unmanned aerial vehicles (UAVs) is of high interest to many governmental and military organizations around the world. An essential aspect of UAV autonomy is the ability for automatic path planning. In this paper, we use the genetic algorithm (GA) and the particle swarm optimization algorithm (PSO) to cope with the complexity of(More)
Recently, the combination of sliding mode and fuzzy logic techniques has emerged as a promising methodology for dealing with nonlinear, uncertain, dynamical systems. In this paper, a sliding mode control algorithm combined with a fuzzy control scheme is developed for the trajectory control of a command guidance system. The acceleration command input is(More)
Metaheuristics are nondeterministic optimization algorithms used to solve complex problems for which classic approaches are unsuitable. Despite their e®ectiveness, metaheuristics require considerable computational power and cannot easily be used in time critical applications. Fortunately, those algorithms are intrinsically parallel and have been implemented(More)
Power distribution networks operate in a radial topology, but also include extra tie switches to allow for their reconfiguration in case of scheduled maintenance or unexpected failure. With the implementation of the smart grid and the development of fast high power switching devices, it is now possible to automatize this reconfiguration to also adjust to(More)
This paper presents the implementation details of a parallel algorithm on graphics processing units (GPUs) to compute the optimal switching angles for the harmonic minimization in multilevel inverters with unequal dc voltage sources. Two algorithms, the Newton-Raphson method and the bisection method, and three different parallel implementations are(More)
This paper proposes an innovative approach for the design of a nonlinear controller to stabilize an autonomous mobile robot. The design approach combines a nonlinear control design method with a root-finding algorithm for nonlinear algebraic equations. For the design, the robot model is divided into two parts: a state space model with intermediate control(More)