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Master's Dissertation
DOI
10.11606/D.3.2016.tde-07032016-104732
Document
Author
Full name
Oscar Wilfredo Rodríguez Rodríguez
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2014
Supervisor
Committee
Garcia, Claudio (President)
Burt, Phillip Mark Seymour
Souza Junior, José Carlos de
Title in Portuguese
Pré-processamento de dados na identificação de processos industriais.
Keywords in Portuguese
Filtragem
Identicação de sistemas
Normalização
Pré-processamento de dados
Reamostragem
Abstract in Portuguese
Neste trabalho busca-se estudar as diferentes etapas de pre-processamento de dados na identificacao de sistemas, que sao: filtragem, normalizacao e amostragem. O objetivo principal e de acondicionar os dados empiricos medidos pelos instrumentos dos processos industriais, para que quando estes dados forem usados na identificacao de sistemas, se possa obter modelos matematicos que representem da forma mais proxima a dinamica do processo real. Vai-se tambem implementar as tecnicas de pre-processamento de dados no software MatLab 2012b e vai-se fazer testes na Planta Piloto de Vazao instalada no Laboratorio de Controle de Processos Industriais do Departamento de Engenharia de Telecomunicacoes e Controle da Escola Politecnica da USP; bem como em plantas simuladas de processos industriais, em que e conhecido a priori seu modelo matematico. Ao final, vai-se analisar e comparar o desempenho das etapas de pre-processamento de dados e sua influencia no indice de ajuste do modelo ao sistema real (fit), obtido mediante o metodo de validacao cruzada. Os parametros do modelo sao obtidos para predicoes infinitos passos a frente.
Title in English
Pre-processing data in the identification of industrial processes.
Keywords in English
Filtering
Identication systems
Preprocessing of data
Resampling
Standardization
Abstract in English
This work aims to study the different stages of data pre-processing in system identification, as are: filtering, normalization and sampling. The main goal is to condition the empirical data measured by the instruments of industrial processes, so that when these data are used to identify systems, one can obtain mathematical models that represent more closely the dynamics of the real process. It will also be implemented the techniques of preprocessing of data in MatLab 2012b and it will be performed tests in the Pilot Plant of Flow at the Laboratory of Industrial Process Control, Department of Telecommunications and Control Engineering from the Polytechnic School of USP; as well as with simulated plants of industrial processes where it is known a priori its mathematical model. At the end, it is analyzed and compared the performance of the pre-processing of data and its influence on the index of adjustment of the model to the real system (fit), obtained by the cross validation method. The model parameters are obtained for infinite step-ahead prediction.
 
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Dissertacao_Oscar.pdf (3.16 Mbytes)
Publishing Date
2016-03-14
 
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