Combined Quadrotor Autopilot System and Differential Morphing System Design

Year 2021, , 64 - 71, 20.12.2021

Oguz Kose , Tugrul Oktay

https://doi.org/10.30518/jav.856436

Cited By: 7

Abstract

The aim of this article is to design and model a quadrotor with autopilot system and differential morphing using the Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm. Along with differential morphing, quadrotor modelling and control was also done. Although it is simple in structure, it has a complex structure in terms of model and control. Newton-Euler method was used for the dynamic model. Non-linear motion equations have been converted to linear motion equations. The full quadrotor model was drawn in the Solidworks program. Mass and moment of inertia information was obtained from this model. Simulation model was created by using state space model approach in Matlab / Simulink environment. Proportional integral derivative (PID) algorithm was used as the control structure. Differential morphing and PID coefficients rates were determined with SPSA. With the optimization method, determining the differential morphing rate, PID coefficients and applying it to the quadrotor provides a very innovative method.

Keywords

Quadrotor, SPSA, PID, Optimization, Morphing

Supporting Institution

Erciyes Üniversitesi

Project Number

FBA-2020-10102

Combined Quadrotor Autopilot System and Differential Morphing System Design

Abstract

The aim of this article is to design and model a quadrotor with autopilot system and differential morphing using the Simultaneous Perturbation Stochastic Approximation (SPSA) optimization algorithm. Along with differential morphing, quadrotor modelling and control was also done. Although it is simple in structure, it has a complex structure in terms of model and control. Newton-Euler method was used for the dynamic model. Non-linear motion equations have been converted to linear motion equations. The full quadrotor model was drawn in the Solidworks program. Mass and moment of inertia information was obtained from this model. Simulation model was created by using state space model approach in Matlab / Simulink environment. Proportional integral derivative (PID) algorithm was used as the control structure. Differential morphing and PID coefficients rates were determined with SPSA. With the optimization method, determining the differential morphing rate, PID coefficients and applying it to the quadrotor provides a very innovative method. 

Keywords

Quadrotor, SPSA, PID, Optimization, Morphing

Project Number

FBA-2020-10102

References

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