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Master's Dissertation
DOI
https://doi.org/10.11606/D.55.2017.tde-01022017-160814
Document
Author
Full name
Diogo Henrique de Melo
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2016
Supervisor
Committee
Costa, Eduardo Fontoura (President)
Siqueira, Adriano Almeida Gonçalves
Toledo, Franklina Maria Bragion de
Vargas, Alessandro do Nascimento
Title in Portuguese
Otimização de consumo de combustível em veículos usando um modelo simplificado de trânsito e sistemas com saltos markovianos
Keywords in Portuguese
Cadeias de Markov
Controle ótimo
Programação dinâmica
Saltos markovianos
Abstract in Portuguese
Esta dissertação aborda o problema de redução do consumo de combustível para veículos. Com esse objetivo, realiza-se o levantamento de um modelo estocástico e de seus parâmetros, o desenvolvimento de um controlador para o veículo, e análise dos resultados. O problema considera a interação com o trânsito de outros veículos, que limita a aplicação de resultados antes disponíveis. Para isto, propõe-se modelar a dinâmica do problema de maneira aproximada, usando sistemas com saltos markovianos, e levantar as probabilidades de transição dos estados da cadeia através de um modelo mais completo para o trânsito no percurso.
Title in English
Optimization of fuel consumption in vehicles using a simplified traffic model and Markov jump system.
Keywords in English
Dynamic programming
Markov chains
Markov jump parameters
Optimal control.
Abstract in English
This dissertation deals with control of vehicles aiming at the fuel consumption optimization, taking into account the interference of traffic. Stochastic interferences like this and other real world phenomena prevents us from directly applying available results. We propose to employ a relatively simple system with Markov jumping parameters as a model for the vehicle subject to traffic interference, and to obtain the transition probabilities from a separate model for the traffic. This dissertation presents the model identification, the solution of the new problem using dynamic programming, and simulation of the obtained control.
 
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Publishing Date
2017-02-01
 
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