A Hybrid Offline Optimization Method for Reconfiguration of Multi-UAV Formations

• Published in: IEEE transactions on aerospace and electronic systems Vol. 57; no. 1; pp. 506 - 520
• Main Authors: Li, Bin, Zhang, Jiangwei, Dai, Li, Teo, Kok Lay, Wang, Song
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Continuous state inequality constraints; control parameterization; Discretization; Electronic mail; formation reconfiguration; Genetic algorithms; hybrid optimization; Inequality; Mathematical model; Optimal control; Optimization; Optimization methods; Particle swarm optimization; Reconfiguration; simulated annealing; unmanned aerial vehicle (UAV); Unmanned aerial vehicles
• ISSN: 0018-9251; 1557-9603
• DOI: 10.1109/TAES.2020.3024427

Formation reconfiguration of multiple unmanned aerial vehicles (UAVs) is a challenging problem. Mathematically, this problem is an optimal control problem subject to continuous state inequality constraints and terminal state equality constraints. The first challenge is that there are an infinite number of constraints to be satisfied for the continuous state inequality constraints, which makes the problem extremely difficult to be solved. The second challenge is that the control and state are usually both been discretized. This will result in noncontinuous control input. In addition, the discretized system may not always accurately approximate the original system. In this article, a hybrid offline optimization scheme is proposed to tackle these problems. Unlike the existing methods, the state variables are not required to be discretized and continuous control inputs can be obtained. In addition, the continuous state inequality constraints are tackled without increasing the total number of constraints. Simulation results show that the proposed hybrid optimization method outperforms the state-of-the-art method—the hybrid particle swarm optimization and genetic algorithm.