PID and predictive control of fixed wing UAVs with segmented control surfaces
Creators: name: Sattar, Abdul
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 400103
subject: Aircraft performance and flight control systems
classificationCode: 400105
subject: Flight dynamics
classificationCode: 401201
subject: Aerodynamics (excl. hypersonic aerodynamics)

description: Small fixed-wing unmanned aerial vehicles (UAVs) have a very distinct capability of long flight endurance due to the inclusion of the main wing. Unlike their multirotor counterparts, the lift force is generated due to the pressure difference between the upper and lower regions of the main wing. Due to uneven pressure distribution profile of atmospheric boundary layers, the aircraft's main wing mostly experiences the turbulent flow of oncoming air during actual outdoor flights. The airplane picks up these turbulent forces, leading to flight path deviation and instability. In order to counteract these undesired forces, the aircraft is equipped with different control surfaces i.e. ailerons, elevator, and rudder. Among these control surfaces, the ailerons are directly attached to the main wing and play a major role in achieving a steady flight.

In this research work, the aileron control surfaces are the center of attention. Given their importance in the flight maneuvering and stability, the ailerons have been segmented into more than two, which is uncommon for a conventional fixed-wing UAV. Unlike the morphing or flexible wing designs, the fixed-wing UAVs with segmented aileron control surfaces provide reduced structural complexity with room to improve flight performance. The rest of this research focuses on designing a robust control system for the fixed-wing UAV with these segmented control surfaces. The small fixed-wing UAVs have very complex nonlinear dynamics making the design of a control system very difficult. One of the viable methods is to use the data obtained from the frequency response tests. This research considers the aircraft a black box model and identifies its dynamics from scratch. A series of sine wave perturbations are injected into the system, and a response is recorded. A set of transfer functions is derived from the acquired responses and later used for the attitude control design.

At first, the attitude controllers are designed and analyzed using reduced-order dynamical models of the aircraft. Although easy to design, the performance of such controllers has been found low as the reduced-order models are not the true representatives of the aircraft's operating range. The study is moved towards the autotuning of the controllers by directly using relay test data. The roll attitude controllers are developed for the inner and outer segments of the UAV with minimal human intervention utilizing the established autotuning rules. Since these controllers rely on the experimental data, all of the aircraft's dynamics from input to the final output are included. This ensures that the actuator dynamics and those from inertial effects of the whole aerial vehicle are included in the final response. Afterward, a heuristic control approach is proposed and implemented to selectively actuate the aileron segments when there are substantial external disturbances.

Considering the multivariable nature of the aircraft, the research is further brought into the domain of model predictive controllers (MPCs). As the given fixed-wing UAV has multiple inputs (segmented ailerons) manipulating single-output (roll motion), the possibility of designing and implementing a MISO controller has been investigated. The best fitting, higher-order transfer functions are employed during the controller design process to acquire maximum performance. The research finds that the resulting controllers have highly stable performance and excellent reference tracking capabilities with minimum overshoots even in the presence of strong wind gusts and extreme step changes.

The last part of this thesis finds the solution to the control allocation problem. As the fixed-wing UAV has two sets of aileron pairs acting as inputs, the control system requires to have suitable knowledge of assigning the control duty to each input. To address this, mid-ranging control has been proposed and implemented for the given aircraft. A complete methodology has been devised for the automatic tuning and integration of various controllers involved in the design process.