Defesa de Dissertação de Mestrado – Juan Gabriel Guerrero Grijalva – 24/05/2017
Defesa de Dissertação de Mestrado | ||
Aluno | Juan Gabriel Guerrero Grijalva | |
Orientador
Coorientador |
Prof. Eugênio de Bona Castelan Neto, Dr. – DAS/UFSC
Prof. Michael Klug, Dr. – IFSC/Joinville |
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Data | 24/05/2017 (quarta-feira) 09h00
Sala PPGEAS II (Piso Inferior) |
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Banca | Prof. Eugênio de Bona Castelan Neto, Dr. – Presidente – DAS/UFSC;
Prof. Henrique Simas, Dr. – EMC/UFSC; Prof. Daniel Ferreira Coutinho, Dr. – UDESC; Prof. Edson Roberto De Pieri, Dr. – DAS/UFSC; |
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Título | Control of Quadrotor using TS Fuzzy Techniques | |
Abstract: Takagi Sugeno (TS) fuzzy techniques have been plenty used successfully in the last decades to control nonlinear mechatronic systems. Therefore, many approaches, in continuous and discrete time, are presented in this work applied in a quadrotor system. Linear matrix inequalities (LMIs) theorems based in Lyapunov functions are used to stabilize the system. Parallel distributed compensation (PDC) is the standard control structure employed through all this work. The fuzzy modeling is based in local nonlinear rules which represent accurately the system. Aiming an efficient processing, it is showed a modeling with a small number of rules without loosing information about the dynamic of the system.
There have been developed many researches in continuous time algorithms for quadrotors. Thus, in this document is considered the hybrid behavior, continuous and discrete-time, of the closed loops system to develop an algorithm which actually could be used in a practical implementation. The sensors are limited by the sampling time (Ts) which is greater than the bandwidth of the processor; then an incorrect selection of the Ts could led in an unnecessary processing or instability. The system could demand constraints in the control input due to the features of the actuators as well as in the output states pitch, roll, yaw and altitude of the quadrotor system. Many ways to deal with these constraints and limitations are showed for controllers based in TS fuzzy model, in which its feedback is computed online or offline. TS fuzzy techniques with PDC are flexible to be used with other control techniques such as model predictive control and poles allocation approaches. Thus, a comparison of these techniques is presented too. Finally, a generic algorithm that could be embedded in any open source processor is presented with numerical simulations. |