NATIONAL AVIATION UNIVERSITY Air navigation Systems Department Theme: Unmanned Aerial Vehicle motion modeling in Matlab/Simulink Supervisor: Done by: Pavlova S.V. Lynnyk T.M.

Where will UAVs be in 2015 ? Wildfire Mapping Disaster management Telecommunication Weather monitoring Aerial imaging/mapping Television news coverage, sporting events. Moviemaking Environmental monitoring The use of UAVs is becoming more popular in both defense and environmental research industries. Also there has been an increase in commercial applications of UAVs. Actuality

However, there is still high development cost. The UAV testing phase has a high budget in the development cycle. There is also high risk that the UAV might be unstable or fail when subjected to different parameters. One cannot be absolutely sure whether the UAV meets the specifications without test flights. This project is a part of solution to the problems outlined. Modeling the UAV dynamics will enable a thorough analysis in the behavior and stability of the UAV at different conditions. Real time simulations will save time, cost and help to eliminate risk. Actuality

Objectives:  Analyze the existing software basis for the UAV motion simulation;  To develop a UAV model using Matlab/Simulink;  Applying engineering and mathematical problem skills;  To estimate longitudinal and lateral stability and control derivatives;  Completing the UAV simulation before the test flight. The aim of graduate work is to give the ability of prediction and improving the static and dynamic stability and control parameters of UAV from the simulation.

With the aim of prediction and improving the static and dynamic stability and control parameters of UAV from the simulation, the next steps were done:  Static and dynamic stability was defined and the UAV components contribution to static and dynamic stability was highlighted.  The Longitudinal and lateral derivatives were defined, estimated and analysed. The derivatives used to simulate the dynamics of the UAV using a Simulink model.  A Simulink model was developed to predict the dynamic characteristic of the existing UAV M-22 “Aerotester”. The inputs to the model were the control surfaces and the atmospheric disturbances.  Thorough analysis of the behaviour and stability of the UAV at different conditions were performed UAV motion modeling Fig. 2 - Dynamic stability Fig. 1 - Oscillatory motions

 The figure 3 graphically shows the elevator response test. The oscillations start after the elevator step input disturbance and continued until the UAV back into the state of equilibrium. There can be observed damped oscillations, it means that M-22 “Aerotester” has positive static and dynamic stability. Results of modeling Figure 3 – Elevator response test.

Results of modeling 2 Figure 4 - Long term response to elevator step input

 The UAV was subjected to various turbulent profiles and it exhibited positive dynamic stability characteristics Results of modeling 3 Figure 5 – Response to turbulance

 The long-term response shows that the M-22 has positive lateral dynamic stability. The UAV settles to zero steady state in 30s after a roll disturbance. There is no overshoot, hence a heavily damped. Results of modeling 4 Figure 6 – Aileron impulse response

During the graduate work performance the analyze of the existing software basis for the UAV motion simulation were done, and on the basis of obtained knowledge UAV model using Matlab/Simulink were developed. The model can be used to simulate any dynamics of any convectional UAV for a various flight conditions. The response to control surface inputs and atmospheric disturbances were determined. The simulations shows that the M-22 “Aerotester” UAV has positive longitudinal dynamic stability for the given flight conditions. M- 22 “Aerotester” UAV reaches equilibrium position in approximately 84 seconds after a step elevator disturbance. The research can be used to develop an advanced UAV capable of different missions. The stability and augmentation study can be used to design a very stable UAV that can also be easily controlled. The simulations can be used for UAV design optimisation, flight testing, and mission simulations. This model offers far more benefits with potential for further development. Conclusion

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