Abstract
We designed a distributed collision‐free formation flight control law in the framework of nonlinear model predictive control. Formation configuration is determined in the virtual reference point coordinate system. Obstacle avoidance is guaranteed by cost penalty, and intervehicle collision avoidance is guaranteed by cost penalty combined with a new priority strategy.
Highlights
Extensive research has been conducted on cooperative control for multiagent systems in the recent years
Obstacle avoidance is guaranteed by cost penalty, and intervehicle collision avoidance is guaranteed by cost penalty combined with a new priority strategy
A collision-free UAV formation flight controller is designed in the framework of MPC
Summary
Extensive research has been conducted on cooperative control for multiagent systems in the recent years. Among the main subproblems of multiple UAVs cooperative control problem, formation flight is of great interest and widely researched 2, 3. The computational effort required for a single optimization can become prohibitive and scales very poorly with the size of the number of unmanned vehicles To address this problem, decentralized model predictive control DMPC method is proposed by breaking the optimization into smaller subproblems. Several researchers exclusively studied UAV formation flight problem in the framework of MPC method 22–28. 23 uses the UAV nonlinear dynamical model in MPC problem formulation and leader-follower structure to design formation flight controller. It uses Karush-Kuhn-Tucker KKT variables to achieve collision avoidance maneuver.
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