Daniel M. Muñoz Arboleda

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Elevator systems are administrated by an elevator group control system (EGCS) and micro-processed sub-systems implementing a local control system (LCS) for each elevator. This paper describes the validation of five dispatching algorithms for elevator systems that were implemented on Spartan 3 FPGA-based boards in an integrated approach reducing the area and(More)
High computational cost for solving large engineering optimization problems point out the design of parallel optimization algorithms. Population based optimization algorithms provide parallel capabilities that can be explored by their implementations done directly in hardware. This paper presents a hardware implementation of Particle Swarm Optimization(More)
Floating-point operations are an essential requisite in a wide range of computational and engineering applications that need good performance and high precision. Current advances in VLSI technology raised the density integration fast enough, allowing the designers to develop directly in hardware several floating-point operations commonly implemented in(More)
Elevator Group Control Systems (EGCSs) manage multiple elevators in a building transporting efficiently passengers. The performance of an EGCS is measured by means of several metrics such as the average waiting time of passengers, the percentage of the passengers waiting more than some predetermined time, power consumption, among others. Four elevator(More)
Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. There are several embedded applications which requires to solve online optimization problems with a high performance. However, the PSO suffers on large execution times, and this fact becomes evident when using(More)
This work describes a hardware architecture for implementing a sequential approach of the Extended Kalman Filter (EKF) that is suitable for mobile robotics tasks, such as self-localization, mapping and navigation problems. As such algorithm is computationally intensive, commonly it is implemented in PC-based platforms to be employed on larger robots. In(More)
Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. However, the PSO algorithm suffers from \emph{premature convergence} and high elapsed time when solving multimodal and large scale engineering problems. This problem becomes an evident drawback for embedded(More)