Estudo e implementação de sistemas de controle para quadricóptero

Data
2018-06-26
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Universidade Federal Rural do Semi-Árido

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The oil and gas industry deals with the transportation and storage of flammable substances at high pressure, requiring continuous monitoring of its structures to avoid damage to the environment, population, economic losses and production stoppages. In view of the current complexity of exploration environments and the continuing necessity of society for products from this sector, the petrochemical industry has been searching for ways to apply automation in order to reduce costs and ensure better security for the environment and the people involved. In this sense, the use of the quadcopter for the inspection and monitoring is an alternative that has been implemented in the last years, consisting of an Unmanned Aerial Vehicle (UAV). Therefore, it is necessary that the quadcopter performs the flight in diverse environments, being a robust and fast response controller in order to avoid the loss of stability and fall. This fact implies the necessity to develop a quadcopter control system that performs control of engine speed and flight altitude. For this reason, we developed and simulated altitude controls, using PID (Proportional Integral Derivative) and Fuzzy Logic control techniques, as well as for speed control of the motors, using a PID controller. To perform the simulation, it was necessary to survey the dynamic modeling of the quadcopter and engines, in order to obtain the approximate mathematical representation of the actual behavior of the vehicle to be controlled. The simulation of systems with controllers was performed using Simulink/MATLAB® software, in which we observed performance parameters such as rise time, overshoot, among others, and compared the responses. Finally, we performed tests on an prototype using the Arduino® platform, in order to verify the behavior of the system. For the altitude control, the simulations showed that with the PID controller we obtain a faster response of the system, but with the Fuzzy controller we obtain a lower overshoot and error. However, this result can not be generalized since the Fuzzy controller depends on the knowledge of a specialist and better answers can be obtained. Regarding the speed control of the motors, the use of the PID controller obtained a faster simulated response and less error when compared to the the system using only the Electronic Speed Controller (ESC). The experimental tests verified the actual behavior of the system with the PID controllers, presenting quantitative deviations to the simulated results due to the presence of disturbances during the flight and the simplifications made in the modeling of the system


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Alves (2018) (ALVES, 2018)