Quadcopter (A-four rotor plane)

Recently, the quadcopter configuration is becoming prevalent for both civilian and military applications, and research is continuing to improve its controllability. However, most the control methodologies depend on accurate system models which are derived from six degrees of freedom nonlinear system dynamics and they generally do not consider realistic outdoor perturbations and uncertainties. As a solution, model-free data-driven system identification and controlling of quadcopter have been refined in this paper. This nonlinear multiple input-multiple output system identification is proliferated using a fuzzy clustering model. The accuracy of the identification is seen to very high. The results of a PID controller used in conjunction with the identified fuzzy model is also presented. The PID controller with the fuzzy identified model is seen to precisely follow the commanded signals.

This paper describes the current legal framework and regulations applied to industrial drone's flights established by different countries as a set point on drones design and applications. We present a mathematical approach used to build the structure of an attitude controller for a quadcopter (drone) as to answer the question of 'How to implement an attitude controller on a quadcopter for indoor and outdoor flights as a step forward to support the safety features in factory applications'. The control system was designed for a quadcopter on ' × ' configuration, which allows it to have six degrees of freedom (6DOF) of movement, while commanded by four inputs given by the radio controller (R/C). Accelerometers and gyroscopes were used in order to obtain the data related to the drone's behavior during the flight to be able to control it. A cascade controller P-PID was implemented in order to control the system and reach the stability as well as in indoor or outdoor flights. The theories presented in this paper were analyzed and proved on a real model resulting in the desired flying behavior.

To properly simulate and implement a quadcopter flight control for intended load and flight conditions, the quadcopter model must have parameters on various relationships including propeller thrust-torque, thrust-PWM, and thrust–angular speed to a certain level of accuracy. Thrust-torque modeling requires an expensive reaction torque measurement sensor. In the absence of sophisticated equipment, the study comes up with alternative methods to complete the quadcopter model. The study also presents a method of modeling the rotational aerodynamic drag on the quadcopter. Although the resulting model of the reaction torque generated by the quadcopter’s propellers and the model of the drag torque acting on the quadcopter body that are derived using the methods in this study may not yield the true values of these quantities, the experimental modeling techniques presented in this work ensure that the derived dynamic model for the quadcopter will nevertheless behave identically with the true model for the quadcopter. The derived dynamic model is validated by basic flight controller simulation and actual flight implementation. The model is used as basis for a quadcopter design, which eventually is used for test purposes of basic flight control. This study serves as a baseline for fail-safe control of a quadcopter experiencing an unexpected motor failure.

larly due to their extension as unmanned aerial vehicles and remotely piloted aerial systems. The critical nature of its flight control is one of the main concerns for its advanced operations. These advanced operations involve on-board stabilization, trajectory tracking, unpredictable changes in the environment, and resilience to noisy data from small sensor systems. In this work, the quadcopter has been considered as a constrained problem, where optimization is required during transition between different set-points of advanced flight control, operations in action and reaction pairs. Firstly, dynamics of quadcopter along with its translational motion have been derived. Secondly, constrained optimization cost function has been set, which is the main building block for deriving the augmented Lagrangian optimization. Thirdly, co-states of the derived constraints are determined to maintain convergence. Performance evaluation showed accuracy of the proposed scheme.

Quadcopter controllers are in use today and in practice they can often cope well in non adverse weather conditions such as lack of strong sudden gusts of wind around the corner of a building or no frequent demands of travel directions by remote control or a guidance law. Different payloads can alter the boundaries of the stable state space region of a drone, its flight envelop, beyond which its autopilot may not be able to regain stable control of the craft. For fixed gain autopilot controllers, reaching the boundary of the flight envelop can be caused by (1) external disturbance like gusts of wind and turbulence, (2) altered drone mass and its distribution and (3) reduction or misalignment of thrust output in the propulsion system caused ware after multiple uses of the drone. This paper introduces symbolic computation to map out the numerical boundaries of controller tolerances in terms of these three factors that affect the autopilots ability to retain stability of the craft. Proof theoretic methods are developed that can be applied to quadcopter of various nominal parameters.

The excellent maneuverability and the availability of a large number of sensors including good quality video cameras make quadcopters attractive for surveillance systems. Most video surveillance systems need a real-time high quality video stream from the cameras on the quadcopter to the base station which requires a stable and reliable radio link. Moreover, to ensure a controlled flight, it is essential to maintain a good quality radio link from the base station to the quad- copter. The quality of this link depends on the distance between base station and quadcopter as well as the ambient noise. Towards this end, we present a controller to hover a quadcopter at the maximum distance from the base station while maintaining the link quality at a given value indicated by the Signal to Noise Ratio (SNR). There are existing solutions in the field of robotics that incorporate the concept of link aware mobility. However, to the best of our knowledge, this is the first link-quality aware mobility implementation on a quadcopter.

The dynamics of a quadcopter are unstable and non-linear. As a result, the quadcopters flight relies heavily on the Flight controller. Here we present a robust control scheme which can act as the flight controller for the quadcopter. We then describe a scheme to translate this scheme into a Spiking Neural Network using a modular approach.

For further comments, visit - http://goo.gl/mkYehR

The recent decrease in the price as well as size of semiconductor logic and due to significant advancements in technologies such as microcontrollers, motors and sensors, the application of quadcopters in several fields has been achieved. However, testing of quadcopter prototypes still has a risk of damage due to faults and unexpected behavior. Hence, a method of testing of quadcopters in simulation mimicking the actual conditions of the real environment in an actual hardware test has been proposed. For this purpose, Gazebo simulator integrated with ROS has been chosen for the simulation of the path of the quadcopter. Moreover, the software Matlab/Simulink has been interfaced with Gazebo in order for the simulation of the quadcopter to be achieved.

The present invention relates to the control of a quadcopter experiencing a failure affecting a pair of rotors. In particular, the invention relates to a computer-implemented method for controlling and stable movement to any coordinate of a quadcopter by actuating a pair of opposing rotors.

A quadcopter comprises a body being configured as a center of mass, a plurality of arms being attached to the body on one end and to a plurality of motors. Also, a plurality of rotors being operably connected individually to the plurality of motors.

Furthermore, a plurality of sensors is being operably connected to a processor. Said processor is being configured to execute a computer-implemented method for controlling and stable movement to any coordinate of a quadcopter by actuating a pair of opposing rotors. Also, said processor is operably connected to the plurality of motors to provide control and movements instructions of the quadcopter. Lastly, a power source is being connected to the processor, the plurality of sensors and the plurality of motors.

In this paper, a TID controller is applied for the trajectory tracking of a quadrotor. The mathematical model of the control system is derived and compared with the traditional PD (Proportional-Derivative) controller. In order to improve the control precision of the UAV, the controller is designed by selecting the proper tuning parameters. To explore the effectiveness of the proposed controller, dynamic responses of a UAV obtained by using the TID controller and the validation of the results compared with the PD controller. The control performances are analysed by using MATLAB/Simulink model.

ADVISER        :Selamet Hariadi S.Kom
DEVELOPER  :Isma Danial H.M

“kini pesawat yang menguhajam ke bumi itu sudah terbang dalam posisi mendatar.”maka, jangan tending-tendang kursi pilot.jangan paksa orang lain mengambil.dont’ do that,karena pilot sudah bertindak benar.saya butu8h tiga tahun untuk menerbangkan pesawat ke ketinggian.tapi saya tak mau jual kecap.”

This paper presents information about
quadrocopter designed for special aim and its applications. In
this context, it focuses basic subjects such as design of a
quadrocopter, obtaining numerical data, detection of foreign
matter on runway. The measurements and graphs belongs to the
subject in point are included. The analyses to be carried out put
forward that the quadrocopter has many fields of use contribute
to safety of aircraft take-off and landing.