Semi-autonomous flight control of forestry-use drone

2019 ◽  
Author(s):  
Masaru Sato ◽  
Masami Iwase
Keyword(s):  
Flight Control ◽  
Autonomous Flight

Flight Control System Design and Autonomous Flight Control of Small-Scale Unmanned Helicopter Based on Nanosensors

2021 ◽  
Vol 16 (4) ◽  
pp. 675-688
Author(s):  
Xinfan Yin ◽  
Xianmin Peng ◽  
Guichuan Zhang ◽  
Binghui Che ◽  
Chang Wang
Keyword(s):  
Control System ◽  
Flight Control ◽  
Control Algorithm ◽  
Installation Space ◽  
Small Scale ◽  
Unmanned Helicopter ◽  
Flight Control System ◽  
Autonomous Flight ◽  
Position Controller ◽  
Attitude Controller

Due to the limitation of the size and power, micro unmanned aerial vehicle (MUAV) usually has a small load capacity. Aiming at the problems of limited installation space and easy being interfered in flight attitude measurement of the small-scale unmanned helicopter (SUH), a low-cost and lightweight flight control system of the SUH based on ARM Cortex-M4 core microcontroller and Micro-Electro-Mechanical Systems (MEMS) sensors is developed in this paper. On this basis, in order to realize the autonomous flight control of SUH, firstly, the mathematical model of the SUH is given by using the Newton-Euler formulation. Secondly, a cascade flight controller consisting of the attitude controller and the position controller is developed based on linear active disturbance rejection control (LADRC) and proportional-integral-derivative (PID) control. Furthermore, simulations are conducted to validate the performance of the attitude controller and the position controller in MATLAB/SIMULINK simulation environment. Finally, based on the Align T-REX 470L SUH experimental platform, the hovering experiment and the route flight experiment are also carried out to validate the performance of the designed flight control system hardware and the proposed control algorithm. The results show that the flight control system designed in this paper has high reliability and strong anti-interference ability, and the control algorithm can effectively and reliably realize the attitude stabilization control and route control of the SUH, with high control accuracy and small error.

Modeling of upset sensor operation for autonomous unmanned systems applications

2019 ◽  
Vol 7 (1) ◽  
pp. 19-34 ◽  
Author(s):  
Mofetoluwa Fagbemi ◽  
Mario G. Perhinschi ◽  
Ghassan Al-Sinbol
Keyword(s):  
Flight Control ◽  
Simulation Environment ◽  
Control Laws ◽  
Content Type ◽  
Autonomous Flight ◽  
Operational Conditions ◽  
Analysis And Design ◽  
Sensor Model ◽  
Comprehensive Framework ◽  
Sensor Modeling

Purpose The purpose of this paper is to develop and implement a general sensor model under normal and abnormal operational conditions including nine functional categories (FCs) to provide additional tools for the design, testing and evaluation of unmanned aerial systems within the West Virginia University unmanned air systems (UAS) simulation environment. Design/methodology/approach The characteristics under normal and abnormal operation of various types of sensors typically used for UAS control are classified within nine FCs. A general and comprehensive framework for sensor modeling is defined as a sequential alteration of the exact value of the measurand corresponding to each FC. Simple mathematical and logical algorithms are used in this process. Each FC is characterized by several parameters, which may be maintained constant or may vary during simulation. The user has maximum flexibility in selecting values for the parameters within and outside sensor design ranges. These values can be set to change at pre-defined moments, such that permanent and intermittent scenarios can be simulated. Sensor outputs are integrated with the autonomous flight simulation allowing for evaluation and analysis of control laws. Findings The developed sensor model can provide the desirable levels of realism necessary for assessing UAS behavior and dynamic response under sensor failure conditions, as well as evaluating the performance of autonomous flight control laws. Research limitations/implications Due to its generality and flexibility, the proposed sensor model allows detailed insight into the dynamic implications of sensor functionality on the performance of control algorithms. It may open new directions for investigating the synergistic interactions between sensors and control systems and lead to improvements in both areas. Practical implications The implementation of the proposed sensor model provides a valuable and flexible simulation tool that can support system design for safety purposes. Specifically, it can address directly the analysis and design of fault tolerant flight control laws for autonomous UASs. The proposed model can be easily customized to be used for different complex dynamic systems. Originality/value In this paper, information on sensor functionality is fused and organized to develop a general and comprehensive framework for sensor modeling at normal and abnormal operational conditions. The implementation of the proposed approach enhances significantly the capability of the UAS simulation environment to address important issues related to the design of control laws with high performance and desirable robustness for safety purposes.

Autonomous Flight Control of Unmanned Small Hobby-Class Helicopter Report 2: Modeling Based on Experimental Identification and Autonomous Flight Control Experiments

2003 ◽  
Vol 15 (5) ◽  
pp. 546-554 ◽  
Author(s):  
Kensaku Hazawa ◽  
◽  
Jinok Shin ◽  
Daigo Fujiwara ◽  
Kazuhiro Igarashi ◽  
...  
Keyword(s):  
Flight Control ◽  
Position Control ◽  
Control Structure ◽  
Controller Design ◽  
Autonomous Flight ◽  
Velocity Models ◽  
Single Output ◽  
Hover Control ◽  
Function Models ◽  
And Control

We developed a small autonomous hobby-class unmanned helicopter that weighs about 9 kg, focusing on attitude and velocity models and controller design. Simge Input Single Output (SISO) transfer function models are derived from brief kinematical analysis and system identification for each of the helicopter dynamics of pitch, roll, yaw, and three direction velocities. We designed six separate controllers based on derived models using LQG and LQI control theory. The models and control structure are verified by experimental results. Accurate position control, namely, hover control and trajectory-following control, is achieved by a simple control algorithm using a designed attitude and velocity control structure. Robustness of the controller against wind was confirmed in a windy-day experiment. To verify robustness against the perturbation of physical helicopter parameters, the controller is applied to a larger helicopter.

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