Yazarlar
- Kose, Oguz(2)
- Oktay, Tugrul(2)
Yayınlar
- MakaleAçık Erişim2021Scopus SJRQ4Quadrotor Flight System Design using Collective and Differential Morphing with SPSA and ANN
Kose, Oguz; Oktay, Tugrul
Quadrotor modeling has been done with collective and differential morphing. Quadrotor initial state and morphing states are drawn in the Solidworks program. Newton-Euler approximation was used for quadrotor modeling. The mass and moment of inertia values required for modeling and simulation were obtained from the Solidworks program. Matlab / Simulink environment and state-space model approaches are used for simulations. A simultaneous perturbation stochastic approximation (SPSA) algorithm was used to determine the quadrotor morphing rates. If the morphing state obtained by SPSA is not included in the values obtained from the drawings, here it is provided to find the moments of inertia with the method based on learning by using the data obtained with the Artificial Neural Network(ANN). Proportional Integral Derivative (PID) is used as the quadrotor control algorithm. PID coefficients are also determined by SPSA.
AtıfScopus13OpenAlex13
İncele - MakaleYalnız künye2020Scopus SJRQ3Simultaneous quadrotor autopilot system and collective morphing system design
Kose, Oguz; Oktay, Tugrul
Purpose: The purpose of this paper is to design a quadrotor with collective morphing using the simultaneous perturbation stochastic approximation (SPSA) optimization algorithm. Design/methodology/approach: Quadrotor design is made by using Solidworks drawing program and some mathematical performance relations. Modelling and simulation are performed in Matlab/Simulink program by using the state space model approaches with the parameters mostly taken from Solidworks. Proportional integral derivative (PID) approach is used as control technique. Morphing amount and the best PID coefficients are determined by using SPSA algorithm. Findings: By using SPSA algorithm, the amount of morphing and the best PID coefficients are determined, and the quadrotor longitudinal and lateral flights are made most stable via morphing. Research limitations/implications: It takes quite a long time to model the quadrotor in Solidworks and Matlab/Simulink with the state space model and using the SPSA algorithm. However, this situation is overcome with the proposed model. Practical implications: Optimization with SPSA is very useful in determining the amount of morphing and PID coefficients for quadrotors. Social implications: SPSA optimization method is useful in terms of cost, time and practicality. Originality/value: It is released to improve performance with morphing, to determine morphing rate with SPSA algorithm and to determine PID coefficients accordingly.
AtıfScopus67WoS64OpenAlex70
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