http://www.esi2.us.es/~rubio/AUT_10_HIQR.pdf

An integral predictive/nonlinear H∞ control structure for a quadrotor helicopter

In this paper, we present a new design method for the flight control of an autonomous quadrotor helicopter based on sliding mode control. Due to the under-actuated property of a quadrotor helicopter, the controller can make the helicopter move three positions (x, y, z) and the yaw angle to their desired values and stabilize the pitch and roll angles. A sliding mode control is proposed to stabilize a class of cascaded under-actuated systems. The global stability analysis of the closed-loop system is presented. The advantage of sliding mode control is its insensitivity to the model errors, parametric uncertainties and other disturbances. Simulations show that the control law robustly stabilizes a quadrotor.

Sliding Mode Control of a Quadrotor Helicopter

This thesis work focused on the study of a quadrotor helicopter. The dynamic system modelling and the control algorithm evaluation were carried out. To test the results, a simulator and a real platform were developed. The Newton-Euler formalism was used to model the dynamic system. Particular attention was given to the group composed of the DC-motor, the gear box and the propeller which needed also the estimation of aerodynamic lift and torque to reach better accuracy. PID control algorithms were compared. The first stage tests were performed on a simulated model where it was easy to evaluate the performance with a mathematical approach. The second stage tests were carried out on the quadrotor platform to evaluate the behavior of the real system. A simulator based on Matlab-Simulink was developed. With this program it was possible to test the accuracy of the model and the robustness of the control algorithms. Furthermore a 3D graphic output and a joystick interface made easier the testability and the observability of the system. A quadrotor platform was developed. The electronics was composed of a Micro Control Unit (MCU) interfaced with several devices: the power supply, the receiving unit, the DC-motor power boards, the Inertial Measurement Unit (IMU), the SONAR and the IR modules. Thanks to these devices and the MCU software, both guided and autonomous flights were possible. (Less)

https://lup.lub.lu.se/student-papers/record/8847641/file/8859343.pdf

Modelling, Identification and Control of a Quadrotor Helicopter

For a quadrotor, one can identify the two well-known inherent rotorcraft characteristics: underactuation and strong coupling in pitch-yaw-roll. To confront these problems and design a station-keeping and tracking controller, dynamic inversion is used. Typical applications of dynamic inversion require the selection of the output control variables to render the internal dynamics stable. This means that in many cases, perfect tracking cannot be guaranteed for the actual desired outputs. Instead, the internal dynamics of the feedback linearised system is stabilised using a robust control term. Unlike standard dynamic inversion, the linear controller gains are chosen uniquely to satisfy the tracking performance. Stability and tracking performance are guaranteed using a Lyapunov-type proof. Simulation with a typical nonlinear quadrotor dynamic model is performed to show the effectiveness of the designed control law in the presence of input disturbances.

https://www.uta.edu/utari/acs/ee5322/lectures/Dynamic%20Inversion%20IET%20CTA%20published%20version.pdf

Dynamic inversion with zero-dynamics stabilisation for quadrotor control

The dynamics of a quadrotor are a simplified form of helicopter dynamics that exhibit the same basic problems of underactuation, strong coupling, multi-input/multi-output design, and unknown nonlinearities. Control design for the quadrotor is more tractable yet reveals corresponding approaches for helicopter and UAV control design. In this paper, a backstepping approach is used for quadrotor controller design. In contrast to most other approaches, we apply backstepping on the Lagrangian form of the dynamics, not the state space form. This is complicated by the fact that the Lagrangian form for the position dynamics is bilinear in the controls. We confront this problem by using an inverse kinematics solution akin to that used in robotics. In addition, two neural nets are introduced to estimate the aerodynamic components, one for aerodynamic forces and one for aerodynamic moments. The result is a controller of intuitively appealing structure having an outer kinematics loop for position control and an inner dynamics loop for attitude control. The control approach described in this paper is robust since it explicitly deals with unmodeled state-dependent disturbances and forces without needing any prior knowledge of the same. A simulation study validates the results obtained in the paper.

Backstepping Approach for Controlling a Quadrotor Using Lagrange Form Dynamics

Presents a nonlinear dynamic model for a four rotors helicopter in a form suited for control design. We show that the input-output decoupling problem is not solvable for this model by means of a static state feedback control law. Then, a dynamic feedback controller is developed which renders the closed-loop system linear, controllable and noninteractive after a change of coordinates in the state-space. Finally, the stability and the robustness of the proposed control law in the presence of wind, turbulences and parametric uncertainties is analyzed through a simulated case study.

V. Mistler

Papers

Exact linearization and noninteracting control of a 4 rotors helicopter via dynamic feedback