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| Author(s): |
Kaio Douglas Teofilo Rocha
Total Authors: 1
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| Document type: | Doctoral Thesis |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Escola de Engenharia de São Carlos (EESC/SBD) |
| Defense date: | 2022-12-16 |
| Examining board members: |
Marco Henrique Terra;
Daniel Ferreira Coutinho;
José Claudio Geromel;
João Yoshiyuki Ishihara;
Tiago Roux de Oliveira
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| Advisor: | Marco Henrique Terra |
| Abstract | |
In the past few years, we have witnessed the rapid popularization of networked cooperative multi-agent systems, which consistently move towards becoming ubiquitous in our society. As one of the most well-established examples of such systems, sensor networks have been applied to increasingly more complex systems, demanding even more robust, efficient, and reliable technologies. Distributed state estimation is the most fundamental task that one can accomplish with these networks. The main objective of this thesis is to develop robust distributed filtering strategies for sensor networks applied to linear discrete-time systems subject to model parametric uncertainties. Specifically, we deal with two types of uncertainties: norm-bounded and polytopic. To achieve this goal, we also address other related problems, divided into two categories. The first category of problems refers to the single-sensor state estimation task. Within this category, we consider the scenarios in which the underlying models are perfectly known and where they are subject to each of the two kinds of uncertainty. We propose nominal and robust filters for each situation. The second category concerns the networks with multiple sensors, considering the same three scenarios. For each one, we propose both centralized and distributed estimators. We use the average consensus algorithm to obtain the distributed filters, which approximate their centralized counterparts. The proposed filters are based on the celebrated Kalman filter and present a similar recursive and relatively simple structure. We evaluate the performance of the proposed estimators with application examples, in which we also compare them to existing strategies from the related literature. (AU) | |
| FAPESP's process: | 17/16346-4 - Communication network fault tolerant control for coordinated movement of heterogeneous robots |
| Grantee: | Kaio Douglas Teófilo Rocha |
| Support Opportunities: | Scholarships in Brazil - Doctorate (Direct) |