Model Predictive Controller of a UAV using the LPV approach

The Unmanned Air Vehicles (UAVs) are being integrated into our society at an increasing rate. The amount of industries that use drones is getting larger every year. Besides the military sector, which was probably the first adopter of drone technology, they are now also being used in the industries such as search and rescue, delivery service, media, civil engineering, etc. In fact, airlines now use drones to perform inspections on aircraft. They fly around airplanes in search of cracks and deformations in the structure. They can also perform such inspections inside an airplane wing, in which fuel is stored. That means that the drone is given a trajectory to follow. That path can be generated live from the cameras on board or it can be a programmed track. However, the fact is that there is a path that the drone receives and so it has to regulate its actuators (rotors) in such a way that the drone follows the trajectory. This is what the thesis is about - to design and implement a controller in MATLAB® that makes the UAV follow the coordinates given to it. The main control strategy used in this thesis will be Model Predictive Control (MPC) that is applied to a drone’s mathematical model in the Linear Parameter Varying (LPV) format. Thanks to this format, it will be possible to apply the most basic MPC strategy, which is suitable for linear systems. Firstly, an attempt is made to control the UAV with a single LPV-MPC controller; however, it will be apparent in the thesis that due to strong nonlinearities, the drone was not able to follow the reference coordinates. Therefore, the controller was separated into two separate controllers. The LPV-MPC strategy was used to control the attitude of the UAV and the feedback linearization strategy was used to control the position of the drone. The validation of the control strategy was performed in MATLAB® in the form of several simulations. Five different tracks were given for the drone to follow. It was then examined how well the UAV followed the given positions, velocities and anglesIncomin

MIMO PID Controller Tuning Method for Quadrotor Based on LQR/LQG Theory

In this work, a new pre-tuning multivariable PID (Proportional Integral Derivative) controllers method for quadrotors is put forward. A procedure based on LQR/LQG (Linear Quadratic Regulator/Gaussian) theory is proposed for attitude and altitude control, which suposes a considerable simplification of the design problem due to only one pretuning parameter being used. With the aim to analyze the performance and robustness of the proposed method, a non-linear mathematical model of the DJI-F450 quadrotor is employed, where rotors dynamics, together with sensors drift/bias properties and noise characteristics of low-cost commercial sensors typically used in this type of applications are considered. In order to estimate the state vector and compensate bias/drift effects in the measures, a combination of filtering and data fusion algorithms (Kalman filter and Madgwick algorithm for attitude estimation) are proposed and implemented. Performance and robustness analysis of the control system is carried out by employing numerical simulations, which take into account the presence of uncertainty in the plant model and external disturbances. The obtained results show the proposed controller design method for multivariable PID controller is robust with respect to: (a) parametric uncertainty in the plant model, (b) disturbances acting at the plant input, (c) sensors measurement and estimation errors

Optimized PID, FOPID and PIDD2 for Controlling UAV Based on SSA

Unmanned aerial vehicles (UAVs) are widely used in recent years for different applications. Thus, UAV control attracted many researchers to suggest suitable controllers.  The simplicity of PID controller makes it the first choice. In this paper, an offline tuning procedure based on Salp swarm algorithm (SSA) for the attitude control of UAV is proposed. The parameters of PID, Fractional order PID (FOPID), and PID Plus Second-order Derivative (PIDD2) have been tuned and their performance is compared in terms of rise time, maximum overshoot, settling time, and integral time absolute error

Internal Model Control Tuned Proportional Integral Derivative for Quadrotor Unmanned Aerial Vehicle Dynamic Model

In recent times, there are has been growing substantive attention to the quadrotor Unmanned Aerial Vehicle (UAV) stability control. However, inherent nonlinearity is a major challenge with this control technique, this paper, therefore, developed a PID based Internal Model Control (IMC) method for the dynamic model of quadrotor UAV. The versatility and simplicity of the Proportional-Integral-Derivative (PID) controller enable it to enjoy wide usage and acceptability as stability control methods for the unmanned aerial vehicles. The aim of this paper is to use the PID controller with IMC to control a UAV. The proposed approach - IMC-PID control method -was simulated using MATLAB software and X-plane flight simulator. Thereafter, a comparative analysis of the IMC-PID control method with Chien-Hrones-Reswick, Cohen-coon, and Ziegler Nichols based PID Controllers was done using pitch and altitude as performance metrics. Keywords: Internal Model Control,MATLAB/Simulink, Proportional Integral Derivative, Quadrotor, Unmanned Aerial Vehicle (UAV),X-Plane, DOI: 10.7176/CTI/9-01 Publication date: April 30th 202

Modeling, identification and navigation of autonomous air vehicles

The main interest of this work is autonomous navigation of autonomous air vehicles, specifically quadrotor helicopters (quadrocopters), and the focus is on convergence to a target destination with collision avoidance. The controller computes a collision-free path leading to the target position and is based on a navigation function approach and waypoints are followed exploiting PID controller

Trajectory tracking control of a quadrotor UAV based on sliding mode active disturbance rejection control

This paper proposes a sliding mode active disturbance rejection control scheme to deal with trajectory tracking control problems for the quadrotor unmanned aerial vehicle (UAV). Firstly, the differential signal of the reference trajectory can be obtained directly by using the tracking differentiator (TD), then the design processes of the controller can be simplified. Secondly, the estimated values of the UAV's velocities, angular velocities, total disturbance can be acquired by using extended state observer (ESO), and the total disturbance of the system can be compensated in the controller in real time, then the robustness and anti-interference capability of the system can be improved. Finally, the sliding mode controller based on TD and ESO is designed, the stability of the closed-loop system is proved by Lyapunov method. Simulation results show that the control scheme proposed in this paper can make the quadrotor track the desired trajectory quickly and accurately. &nbsp

Control of an UAV using LPV techniques

Se explorara la aplicación de técnicas de LPV para el control de un UAV. El controlador será implementado tanto en simulación como en un equipo real. Según las necesidades encontradas se probaran diferentes arquitecturas de control

Mathematical & Physical Modelling of a Quadrotor UAV

Unmanned aerial vehicles (UAVs) are now becoming a major topic of interest due to their flying capabilities attracting researchers who are working within various application. Quadrotors in particular are one of main types of UAVs that are now currently studied, where some of the main focuses are positional and attitude tracking. Currently, verifying these systems in simulation is generally processed through MATLAB/Simulink where the dynamics are thoroughly analyzed. In this paper, the results attained from the mathematical dynamics implemented in Simulink will be justified using ADAMS environment. This software was purposely developed to accurately model the dynamics of mechanical systems in 3D without considering any equations of motion. SolidWorks is used to design the quadrotor frame that satisfies the properties of the proposed system in Simulink. Setting the control inputs as angular velocity of each motor will generate a relative thrust in order for the vehicle to achieve motion. Finally, the dynamic behavior on ADAMS and Simulink are compared as the control inputs are identically applied, which has revealed a marginal difference between the resultant motions

Sliding mode control design for the attitude and altitude of the quadrotor UAV

Recently, the quadrotor unmanned aerial vehicles (UAV) are attracting significant interest from researchers due to its widespread applications, which involve the civilian and military sectors. In this paper, a robust sliding mode control (SMC) algorithm is designed to stabilize the attitude and track the altitude of quadrotor UAV. The switching function in the SMC control law has been replaced by the error function to reduce the chattering influences. The chattering phenomenon is induced by the parameter uncertainties and external disturbances and results in critical issues, for instance, the vibration in the mechanical components. The simulation results of the traditional SMC and feedback linearization (FBL) are used as the benchmark to test and evaluate the performance of the proposed SMC, which proved that the proposed controller outperforms the traditional SMC and FBL controllers