A collision-free formation reconfiguration control approach for Unmanned Aerial Vehicles

To adapt the complexity and flexibility of battlefield environment, a method of formation reconfiguration based on Rapidly-exploring Random Tree (RRT) algorithm is proposed, which shows the advantage of formation of Unmanned Aerial Vehicles (UAVs). Firstly, the kinematic model for UAVs is built, and the feasibility of combination of traditional RRT algorithm and formation reconfiguration of UAVs is analyzed. Secondly, the strategies of trajectory correction comprising node removal and transition trajectory are adopted. Then the dynamic and collision avoidance constraints are discussed respectively, which are essential for exploring the process of RRT algorithm as well as adjusting the trajectory of UAVs. Finally, the simulation and flight experiment are carried out to verify the effectiveness of the proposed method. The results show that the reconfiguration method is able to achieve the formation reconfiguration rapidly and safely. Moreove, the planed trajectory can satisfy the tracing requirement, which is of significance for flight of UAVs in the battlefield environment.

Download Full-text

Adaptive attitude controller design for tail-sitter unmanned aerial vehicles

Journal of Vibration and Control ◽

10.1177/1077546320925350 ◽

2020 ◽

pp. 107754632092535

Author(s):

Deyuan Liu ◽

Hao Liu ◽

Jiansong Zhang ◽

Frank L Lewis

Keyword(s):

Adaptive Control ◽

Unmanned Aerial Vehicles ◽

Control Method ◽

Controller Design ◽

Dynamic Pressure ◽

Tracking Errors ◽

Control Approach ◽

Aerial Vehicles ◽

Attitude Tracking ◽

Mode Transitions

Tail-sitter unmanned aerial vehicles have two flight modes: they can fly long distances at high cruising speeds as fixed-wing aircrafts; or hover, take off, and land vertically as rotary-wing aircrafts. The tail-sitter dynamics involves serious nonlinearities and high uncertainties, especially in the two flight mode transitions. In this article, an adaptive control approach is proposed for a class of tail-sitter unmanned aerial vehicles to achieve the robustness properties. The control torque allocation problem is addressed based on the dynamic pressure in the transition flight. The proposed control method does not need to switch the coordinate system, the controller structure, or the controller parameters in different flight modes. It is proven that the attitude tracking errors can converge into a given neighborhood of the origin in finite time. Simulation results are presented to show the advantages of the proposed adaptive control method.

Download Full-text

Trophallaxis network control approach to formation flight of multiple unmanned aerial vehicles

Science China Technological Sciences ◽

10.1007/s11431-013-5199-0 ◽

2013 ◽

Vol 56 (5) ◽

pp. 1066-1074 ◽

Cited By ~ 29

Author(s):

HaiBin Duan ◽

QiNan Luo ◽

YaXiang Yu

Keyword(s):

Unmanned Aerial Vehicles ◽

Network Control ◽

Formation Flight ◽

Control Approach ◽

Aerial Vehicles ◽

Multiple Unmanned Aerial Vehicles

Download Full-text

Modeling and Simulation of Perching With a Quadrotor Aerial Robot With Passive Bio-inspired Legs and Feet

ASME Letters in Dynamic Systems and Control ◽

10.1115/1.4046778 ◽

2020 ◽

Vol 1 (2) ◽

Author(s):

David J. Dunlop ◽

Mark A. Minor

Keyword(s):

Unmanned Aerial Vehicles ◽

Control Approach ◽

Planning And Control ◽

Aerial Vehicles ◽

Physical Experiments ◽

Control Research ◽

Physical Prototype ◽

And Control ◽

Future Work ◽

Quadrotor System

Abstract Perching in unmanned aerial vehicles is appealing for reconnaissance, monitoring, communications, and charging. This paper focuses on modeling, simulation, and control of bioinspired perching in unmanned aerial vehicles on cylindrical objects, which will be used for future planning and control research. A modular approach is taken where the quadrotor, legs, feet, and toes are modeled separately and then integrated to form a complete simulation system. New models of these components consider kinematics and dynamics of each element and their coupling through tendons that provide actuation. The integrated model is assembled to simulate a physical prototype and then validated based upon physical experiments to provide calibration. Simulation results evaluate the validated model performing perching with different gripper-perch alignments. The simulation environment developed in this research provides a foundation to research control approaches for use with the discussed passive perching mechanism. The simulation was validated to capture the dynamics of the real perching mechanism. This platform will be used in future work to develop a control approach that will be implemented in a quadrotor system to land and take-off from a perch in a reliable manner.

Download Full-text