578 research outputs found
Four Tilting Rotor Convertible MAV: Modeling and Real-Time Hover Flight Control
International audienceThis paper describes the modeling, control and hardware implementation of an experimental tilt-rotor aircraft. This vehicle combines the high-speed cruise capabilities of a conventional airplane with the hovering capabilities of a helicopter by tilting their four rotors. Changing between cruise and hover flight modes in mid-air is referred to transition. Dynamic model of the vehicle is derived both for vertical and horizontal flight modes using Newtonian approach. Two nonlinear control strategies are presented and evaluated at simulation level to control, the vertical and horizontal flight dynamics of the vehicle in the longitudinal plane. An experimental prototype named Quad-plane was developed to perform the vertical flight. A low-cost DSP-based Embedded Flight Control System (EFCS) was designed and built to achieve autonomous attitude-stabilized flight
A novel approach to the control of quad-rotor helicopters using fuzzy-neural networks
Quad-rotor helicopters are agile aircraft which are lifted and propelled by four rotors. Unlike traditional helicopters, they do not require a tail-rotor to control yaw, but can use four smaller fixed-pitch rotors. However, without an intelligent control system it is very difficult for a human to successfully fly and manoeuvre such a vehicle. Thus, most of recent research has focused on small unmanned aerial vehicles, such that advanced embedded control systems could be developed to control these aircrafts. Vehicles of this nature are very useful when it comes to situations that require unmanned operations, for instance performing tasks in dangerous and/or inaccessible environments that could put human lives at risk. This research demonstrates a consistent way of developing a robust adaptive controller for quad-rotor helicopters, using fuzzy-neural networks; creating an intelligent system that is able to monitor and control the non-linear multi-variable flying states of the quad-rotor, enabling it to adapt to the changing environmental situations and learn from past missions. Firstly, an analytical dynamic model of the quad-rotor helicopter was developed and simulated using Matlab/Simulink software, where the behaviour of the quad-rotor helicopter was assessed due to voltage excitation. Secondly, a 3-D model with the same parameter values as that of the analytical dynamic model was developed using Solidworks software. Computational Fluid Dynamics (CFD) was then used to simulate and analyse the effects of the external disturbance on the control and performance of the quad-rotor helicopter. Verification and validation of the two models were carried out by comparing the simulation results with real flight experiment results. The need for more reliable and accurate simulation data led to the development of a neural network error compensation system, which was embedded in the simulation system to correct the minor discrepancies found between the simulation and experiment results. Data obtained from the simulations were then used to train a fuzzy-neural system, made up of a hierarchy of controllers to control the attitude and position of the quad-rotor helicopter. The success of the project was measured against the quad-rotorâs ability to adapt to wind speeds of different magnitudes and directions by re-arranging the speeds of the rotors to compensate for any disturbance. From the simulation results, the fuzzy-neural controller is sufficient to achieve attitude and position control of the quad-rotor helicopter in different weather conditions, paving way for future real time applications
Advanced Feedback Linearization Control for Tiltrotor UAVs: Gait Plan, Controller Design, and Stability Analysis
Three challenges, however, can hinder the application of Feedback
Linearization: over-intensive control signals, singular decoupling matrix, and
saturation. Activating any of these three issues can challenge the stability
proof. To solve these three challenges, first, this research proposed the drone
gait plan. The gait plan was initially used to figure out the control problems
in quadruped (four-legged) robots; applying this approach, accompanied by
Feedback Linearization, the quality of the control signals was enhanced. Then,
we proposed the concept of unacceptable attitude curves, which are not allowed
for the tiltrotor to travel to. The Two Color Map Theorem was subsequently
established to enlarge the supported attitude for the tiltrotor. These theories
were employed in the tiltrotor tracking problem with different references.
Notable improvements in the control signals were witnessed in the tiltrotor
simulator. Finally, we explored the control theory, the stability proof of the
novel mobile robot (tilt vehicle) stabilized by Feedback Linearization with
saturation. Instead of adopting the tiltrotor model, which is over-complicated,
we designed a conceptual mobile robot (tilt-car) to analyze the stability
proof. The stability proof (stable in the sense of Lyapunov) was found for a
mobile robot (tilt vehicle) controlled by Feedback Linearization with
saturation for the first time. The success tracking result with the promising
control signals in the tiltrotor simulator demonstrates the advances of our
control method. Also, the Lyapunov candidate and the tracking result in the
mobile robot (tilt-car) simulator confirm our deductions of the stability
proof. These results reveal that these three challenges in Feedback
Linearization are solved, to some extents.Comment: Doctoral Thesis at The University of Toky
Voliro: An Omnidirectional Hexacopter With Tiltable Rotors
Extending the maneuverability of unmanned areal vehicles promises to yield a
considerable increase in the areas in which these systems can be used. Some
such applications are the performance of more complicated inspection tasks and
the generation of complex uninterrupted movements of an attached camera. In
this paper we address this challenge by presenting Voliro, a novel aerial
platform that combines the advantages of existing multi-rotor systems with the
agility of omnidirectionally controllable platforms. We propose the use of a
hexacopter with tiltable rotors allowing the system to decouple the control of
position and orientation. The contributions of this work involve the mechanical
design as well as a controller with the corresponding allocation scheme. This
work also discusses the design challenges involved when turning the concept of
a hexacopter with tiltable rotors into an actual prototype. The agility of the
system is demonstrated and evaluated in real- world experiments.Comment: Submitted to Robotics and Automation Magazin
Unified incremental nonlinear controller for the transition control of a hybrid dual-axis tilting rotor quad-plane
Overactuated Tilt Rotor Unmanned Aerial Vehicles are renowned for exceptional
wind resistance and a broad operational range, which poses complex control
challenges due to non-affine dynamics. Traditional solutions employ multi-state
switched logic controllers for transitions. Our study introduces a novel
unified incremental nonlinear controller for overactuated dual-axis tilting
rotor quad-planes, seamlessly managing pitch, roll, and physical actuator
commands. The control allocation problem is addressed using a SQP iterative
optimization algorithm, well-suited for nonlinear actuator effectiveness in
thrust vectoring vehicles. The controller design integrates desired roll and
pitch angle inputs. These desired attitude angles are autonomously managed by
the controller and then conveyed to the vehicle during slow airspeed phases,
when the vehicle maintains its 6 DOF. We incorporate an AoA protection logic to
prevent wing stall and a yaw rate reference model for coordinated turns. Flight
tests confirm the controller's effectiveness in transitioning from hovering to
forward flight, achieving desired vertical and lateral accelerations, and
reverting to hovering
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