Fractional Order Flight Control of a Small Fixed-Wing UAV: Controller Design and Simulation Study

2009 ◽  
Author(s):  
Haiyang Chao ◽  
Ying Luo ◽  
Long Di ◽  
YangQuan Chen
Keyword(s):  
Fractional Order ◽  
Flight Control ◽  
Controller Design ◽  
Design Method ◽  
Simulation Studies ◽  
Order Model ◽  
Small Uav ◽  
Aerial Vehicle ◽  
Fractional Order Pi Controller ◽  
Fractional Order Controller

This paper focuses on designing and implementation of fractional order proportional integral (PIα) flight controller on a small fixed-wing unmanned aerial vehicle (UAV). It describes mainly the controller design and simulation studies. The basics of UAV flight control are introduced first with a special emphasis on small UAV platforms. Time domain system identification methods are tried on the UAV roll channel. A new fractional order PI controller design method is then provided based on the identified first order model. The fractional order PIα controller can outperform the traditional integer order PID controller because it has a larger memory and more candidate solutions to choose. The simulation results show the effectiveness of the proposed controller design strategy and the robustness of fractional order controller under conditions of wind gusts and various pay-loads.

scholarly journals Novel Optimum Magnitude Based Fractional Order Controller Design Method

2018 ◽  
Vol 51 (4) ◽  
pp. 912-917 ◽  
Author(s):  
Eva-H. Dulf ◽  
Mircea Șușcă ◽  
Levente Kovács
Keyword(s):  
Fractional Order ◽  
Controller Design ◽  
Design Method ◽  
Fractional Order Controller

scholarly journals Robust H∞ Optimal Controller Design for The Small Unmanned Aerial Vehicle

2018 ◽  
Vol 23 (4) ◽  
pp. 313-322
Author(s):  
Róbert Szabolcsi
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Control Systems ◽  
Flight Control ◽  
Controller Design ◽  
Controller Synthesis ◽  
Optimal Controller ◽  
Flight Control System ◽  
Design Procedures ◽  
Small Uav ◽  
Aerial Vehicle

Abstract This article deals with robust H∞ optimal control of the flight control systems of the small unmanned aerial vehicles (UAVs) in the presence of the plant disturbances and sensor noises. The rationales of the theory of H∞ controller synthesis are brought into a unique frame supporting design procedures being implemented. The paper focuses on numerical example of the synthesis of the controller of the flight control system of the small UAV.

Altitude Controller Design for Quadcopter UAV

2015 ◽  
Vol 74 (1) ◽  
Author(s):  
Muhammad Zaki Mustapa
Keyword(s):  
Real Time ◽  
Attitude Control ◽  
Controller Design ◽  
Design Method ◽  
Time Windows ◽  
The Real ◽  
Data Acquisition Card ◽  
Aerial Vehicle ◽  
Hovering Control ◽  
Real Time Application

This paper discusses on attitude control of a quadcopter unmanned aerial vehicle (UAV) in real time application. Newton-Euler equation is used to derive the model of system and the model characteristic is analyzed. The paper describes the controller design method for the hovering control of UAV automatic vertical take-off system. In order to take-off the quadcopter and stable the altitude, PID controller has been designed. The scope of study is to develop an altitude controller of the vertical take-off as realistic as possible. The quadcopter flight system has nonlinear characteristics. A simulation is conducted to test and analyze the control performance of the quadcopter model. The simulation was conducted by using Mat-lab Simulink. On the other hand, for the real time application, the PCI-1711 data acquisition card is used as an interface for controller design which routes from Simulink to hardware. This study showed the controller designs are implemented and tuned to the real system using Real Time Windows Target approach by Mat-Lab Simulink.

scholarly journals Lead and lag controller design in fractional-order control systems

2019 ◽  
Vol 52 (7-8) ◽  
pp. 1017-1028
Author(s):  
Tufan Dogruer ◽  
Nusret Tan
Keyword(s):  
Control System ◽  
Control Systems ◽  
Fractional Order ◽  
Fourth Order ◽  
Controller Design ◽  
Design Method ◽  
Performance Criteria ◽  
Order System ◽  
Fractional Order Control ◽  
Minimum Error

This paper presents a controller design method using lead and lag controllers for fractional-order control systems. In the presented method, it is aimed to minimize the error in the control system and to obtain controller parameters parametrically. The error occurring in the system can be minimized by integral performance criteria. The lead and lag controllers have three parameters that need to be calculated. These parameters can be determined by the simulation model created in the Matlab environment. In this study, the fractional-order system in the model was performed using Matsuda’s fourth-order integer approximation. In the optimization model, the error is minimized by using the integral performance criteria, and the controller parameters are obtained for the minimum error values. The results show that the presented method gives good step responses for lead and lag controllers.

scholarly journals The Study of Fractional Order Controller with SLAM in the Humanoid Robot

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Shuhuan Wen ◽  
Xiao Chen ◽  
Yongsheng Zhao ◽  
Ahmad B. Rad ◽  
Kamal Mohammed Othman ◽  
...  
Keyword(s):  
Transfer Function ◽  
Power Series ◽  
Fractional Order ◽  
Humanoid Robot ◽  
Power Series Expansion ◽  
Pi Controller ◽  
Fractional Order Pi Controller ◽  
Fractional Order Controller ◽  
Accumulated Error ◽  
Fopi Controller

We present a fractional order PI controller (FOPI) with SLAM method, and the proposed method is used in the simulation of navigation of NAO humanoid robot from Aldebaran. We can discretize the transfer function by the Al-Alaoui generating function and then get the FOPI controller by Power Series Expansion (PSE). FOPI can be used as a correction part to reduce the accumulated error of SLAM. In the FOPI controller, the parameters (Kp,Ki,  and  α) need to be tuned to obtain the best performance. Finally, we compare the results of position without controller and with PI controller, FOPI controller. The simulations show that the FOPI controller can reduce the error between the real position and estimated position. The proposed method is efficient and reliable for NAO navigation.

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