NMPC-PID based new control structure design for altitude and attitude stabilization of non-linear quad-rotor type unmanned aerial vehicles (UAV) - Muhammad Hassan Tanveer (School of Mechatronic Engineering, Universiti Malaysia Perlis, 2013)
Quad-rotor typed unmanned aerial vehicles (UAV) are rotorcraft that has four propellers. In this design there are two arms and each arm has two propellers at their end.. It has complex controlling structure, that is why this rotorcraft is overall non-linear in nature. Hence, it creates a lot of difficulties during flying and become very difficult to make it fly stabilize under different sort of uncertainties. Therefore, stabilization of non-linear UAV system under various uncertainties like wind burst, system and sensor noise conditions has been a challenging research domain among the researchers and many of research work has been done in this domain, but still there is a lot of room available in this area. The objective of this research is to develop a stable control algorithm for Quad-rotor attitude and altitude stabilization. To solve its stability problem, the important role is done by making a control algorithm which satisfies its control system requirements. In this thesis, the Newton-Euler formalism was used to model the dynamic of Quad-rotor system and then a robust with more accurate control for stabilization of non-linear UAV system is intended. The proposed control technique is divided into two sub-systems. In order to validate the disturbance rejection operation, a robust Proportional, Integral and Derivative (PID) controller is derived in first phase of proposed system. Then for the removal of unwanted sensor and system noises, Non-Linear Model Predictive Control (NMPC) control algorithm is used which works on the technique of minimizing the cost criterion function. It is shown that proposed NMPC-PID based control technique results in a more robust stable control system and to verify the effectiveness of proposed technique on UAV system, it is simulated on MATLAB-Simulink environment which confirms and verify improvements in quality and effectiveness of the proposed method.