Defesa de Dissertação de Mestrado – Rodrigo da Silva Gesser – 05/07/2018
05/07/2018 17:22
| Defesa de Dissertação de Mestrado | |
| Aluno | Rodrigo da Silva Gesser |
| Orientador
Coorientador |
Prof. Julio Elias Normey-Rico, Dr. – DAS/UFSC
Prof. Daniel Martins Lima, Dr. – DAS/UFSC |
| Data | 05/07/2018 (quinta-feira) – 13h30
Sala PPGEAS I (piso superior) |
| Banca | Prof. Julio Elias Normey-Rico, Dr. – Presidente – DAS/UFSC;
Prof. Marcelo Lopes de Lima, Dr. – Petrobras; Prof. Alexandre Trofino Neto, Dr. – DAS/UFSC; Prof. Gustavo Arthur de Andrade, Dr. – DAS/UFSC; Prof. Paulo Renato da Costa Mendes, Dr. – DAS/UFSC (suplente). |
| Título | Robust Model Predictive Control: a Comparative Study considering Implementation Issues |
| Abstract: Robust Model Predictive Control (RMPC) is related to a variety of methods designed to guarantee control performance using optimization algorithms while considering systems with uncertainties. Many RMPC methods were created with different formulations, however there is lack of studies comparing their performances using pre-established metrics. Thus, the objective of this work is to analyze and compare different RMPC methods for different systems. The methods are sorted by Min-max RMPC, Tube-based RMPC, LMI-based RMPC and Cost-contractive RMPC, which were carefully chosen based on their relevance in the current literature. The metrics used to compare the methods are separated in off-line, related to configuration of the controller prior to its use, and on-line, which are related to the computational cost of the algorithm and difficulties that may arise during its application. Firstly, it is realized a thorough comparison of the RMPC methods for SISO systems, observing the behavior of the algorithms for distinct scenarios. Then, the RMPC methods are analyzed for a MIMO case study, the Continuous Stirred Tank Reactor (CSTR), using a realistic non-linear model of the process. | |
