The aim of this study is to design an autopilot system for Unmanned Aerial Vehicle (UAV) in a small size and to compare the efficiency of the systems designed with different methods. For this purpose, linearized equations of motion for a small size UAV has beeen firstly obtained. Then the state space equations are used to check the stability characteristics of the UAV. Using the classical method, the longitudinal pitch angle, altitude and speed controller are designed for separate transfer functions according to the location curve of the roots and the desired response values. PID values were determined by considering the response of the system using classical methods. On the other hand, a feedback control system has been designed to improve the stability of different lines. And also an orientation controller has been designed. New approach proposed in the study is Adaptive Network Based Fuzzy Inference Systems (ANFIS) controller. In this study, a new controller approach based on fuzzy logic is proposed. Four data sets, PID control inputs and control sign have been obtained for the design of the proposed controller. These data sets have been used for training the fuzzy controller. As a result; It is presented with graphs that the proposed method is applicable and gives successful results.
UAV (Unmanned Aerial Vehicle) Dynamic Model State Space Model ANFIS
The aim of this study is to design an autopilot system for Unmanned Aerial Vehicle (UAV) in a small size and to compare the efficiency of the systems designed with different methods. For this purpose, linearized equations of motion for a small size UAV has beeen firstly obtained. Then the state space equations are used to check the stability characteristics of the UAV. Using the classical method, the longitudinal pitch angle, altitude and speed controller are designed for separate transfer functions according to the location curve of the roots and the desired response values. PID values were determined by considering the response of the system using classical methods. On the other hand, a feedback control system has been designed to improve the stability of different lines. And also an orientation controller has been designed. New approach proposed in the study is Adaptive Network Based Fuzzy Inference Systems (ANFIS) controller. In this study, a new controller approach based on fuzzy logic is proposed. Four data sets, PID control inputs and control sign have been obtained for the design of the proposed controller. These data sets have been used for training the fuzzy controller. As a result; It is presented with graphs that the proposed method is applicable and gives successful results.
UAV (Unmanned Aerial Vehicle) Dynamic Model State Space Model ANFIS
Birincil Dil | İngilizce |
---|---|
Konular | Mühendislik |
Bölüm | Makaleler |
Yazarlar | |
Yayımlanma Tarihi | 31 Aralık 2019 |
Yayımlandığı Sayı | Yıl 2019 Sayı: 17 |