Receding-Horizon Trajectory Planning for Multiple UAVs Using Particle Swarm Optimization

2019 ◽  
Author(s):  
Dileep M. Vijayakumari ◽  
Seungkeun Kim ◽  
Jinyoung Suk ◽  
Hyemin Mo
Keyword(s):  
Particle Swarm Optimization ◽  
Trajectory Planning ◽  
Particle Swarm ◽  
Receding Horizon ◽  
Swarm Optimization ◽  
Multiple Uavs

A trajectory planning model of tiltrotor considering multi-phase and multi-mode flight

2019 ◽  
Vol 233 (16) ◽  
pp. 6019-6031
Author(s):  
Jing Zhang ◽  
Wu Yu ◽  
Xiangju Qu
Keyword(s):  
Particle Swarm Optimization ◽  
Trajectory Planning ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Model Simulation ◽  
Particle Swarm ◽  
Planning Model ◽  
Swarm Optimization ◽  
Multi Phase ◽  
Multi Mode

A trajectory planning model of tiltrotor with multi-phase and multi-mode flight is proposed in this paper. The model is developed to obtain the trajectory of tiltrotor with consideration of flight mission and environment. In the established model, the flight mission from take-off to landing is composed of several phases which are related to the flight modes. On the basis of the flight phases and the flight modes, the trajectory planning model of tiltrotor is described from three aspects: i.e. tiltrotor dynamics including motion equations and maneuverability, flight mission requirements, and flight environment including different no-fly zones. Then, particle swarm optimization algorithm is applied to generate the trajectory of tiltrotor online. The strategy of receding horizon optimization is adopted, and the control inputs in the next few seconds are optimized by particle swarm optimization algorithm. Flight mission simulations with different situations are carried out to verify the rationality and validity of the proposed trajectory planning model. Simulation results demonstrate that the tiltrotor flying with multi-mode can reach the target in three cases and can avoid both static and dynamic obstacles.

Design of Multi-Criteria PI Controller Using Particle Swarm Optimization for Multiple UAVs Close Formation

2010 ◽  
Vol 1 (2) ◽  
pp. 1-17
Author(s):  
Xiangyin Zhang ◽  
Haibin Duan ◽  
Shan Shao ◽  
Yunhui Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Absolute Error ◽  
Pi Controller ◽  
Formation Flight ◽  
Swarm Optimization ◽  
Formation Tracking ◽  
Multiple Uavs ◽  
On Line ◽  
Uninhabited Aerial Vehicles

Close formation flight is one of the most complicated problems on multiple Uninhabited Aerial Vehicles (UAVs) coordinated control. This paper proposes a new method to achieve close formation tracking control of multiple UAVs by applying Particle Swarm Optimization (PSO) based Proportional plus Integral (PI) controller. Due to its simple structure and effectiveness, multi-criteria PI control strategy is employed to design the controller for multiple UAVs formation, while PSO is used to optimize the controller parameters on-line. With the inclusion of overshoot, rise time, and system accumulated absolute error in the multi-criteria performance index, the overall performance of multi-criteria PI controller is optimized to be satisfactory. Simulation results show the feasibility and effectiveness of the proposed approach.

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