Vincent Roberge

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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)
In this paper, we present a parallel implementation of the Particle Swarm Optimization (PSO) on GPU using CUDA. By fully utilizing the processing power of graphic processors, our implementation provides a speedup of 215x compared to a sequential implementation on CPU. This speedup is significantly superior to what has been reported in recent papers and 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)
Power distribution networks are typically structured in a radial topology with extra tie switches to allow for a manual reconfiguration in case of unexpected failure or scheduled maintenance. With the implementation of the smart grid, it is now realistic to also consider the power demand fluctuation and have real-time reconfiguration of the network to(More)
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