About Me

Mon, 01 Jan 0001 00:00:00 +0000

I received my Bachelor of Science degree in Control and Automation Engineering from University of Brasília (UnB) in 2008, being awarded with the best student prize, given by the Faculty of Technology and the Rector of University of Brasília.

In 2007, I was accepted to the Internship Program of Johnson Controls’ building efficiency division (Brasília branch) and, just after graduating, I was hired as an Application Engineer. In this position, I designed and commissioned a myriad of building automation systems, managed the installation teams, and participated in the drafting of the winning technical proposal for the Local Area Network bidding process of Quito’s New International Airport.

Publications

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Ph.D. Thesis

Chagas, R. A. J. (2012)

Distributed Estimation of Errors in Aided Inertial Navigation Systems

Instituto Tecnológico de Aeronáutica · Doctoral Thesis (in Portuguese)

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A distributed sensors network estimating dynamic processes achieves a higher level of robustness. In this scenario, if a particular node fails, the information from the network can prevent significant degradation or interruption of the estimation process. The literature has a myriad of algorithms to fuse information in a distributed sensors network in which each node is measuring the same dynamic process. There are also proposed methods to fuse such information when it is shared, with delays, among the nodes. However, to the best knowledge of the author, algorithms have not yet been developed to perform distributed estimation in a sensor network with communication delays in which each node measures a different yet related dynamic process. Many interesting applications fit this scenario, for example, a swarm of unmanned aerial vehicles (UAVs) flying in formation and outfitted with communication devices. Therefore, this investigation aimed at developing techniques to fuse delayed measurements in sensor networks in which the nodes do not share the same dynamics model. Two novel algorithms have been proposed: measurement extrapolation and measurement transportation. These techniques have been compared to a classical approach to fuse delayed measurements in a Kalman filter, which is optimal by construction, and has been adapted to the aforementioned distributed scenario. First, the algorithms have been analyzed theoretically by deriving their expected performance, memory requirements, and computational workload based on floating point operations. Afterwards, the algorithms have been tested using a simplified numerical example for initial validation. Then, a UAV formation has been simulated to perform the role of a sensor network with aircraft exchanging delayed GNSS sensor measurements and relative positions. The two novel, sub-optimal algorithms have been numerically compared with the optimal approach in terms of accuracy and computational workload. The sub-optimal algorithms have fused properly the delayed measurements and limited the navigation errors, whereas the computational load has been significantly lower than that of the classical, optimal approach. Measurement extrapolation performance has been severely degraded when subjected to a significant communication delay. On the other hand, measurement transportation performance has been very similar to that of the classical approach in all simulated scenarios. Thus, this investigation indicates that the developed techniques improve the cost/benefit relative to the optimal algorithm for the aforementioned scenarios with both small and large delays.

Ronan Arraes Jardim Chagas, Ph.D.

About Me

Publications

Ph.D. Thesis