Abstract
Coordinated planning is a key technology for multiple Unmanned Combat Aerial Vehicles (UCAVs) control problem. In this paper, the velocity of each UCAV is planned to coordinate the sequence, in which the UCAVs pass their critical waypoints. The coordinated planning problem is formulated as a multi-objective optimal one. The objective consists in minimizing the total risk and the difference between the average and expected velocity of each UCAV. The acceleration ability of an UCAV is treated as the problem constraint. A steady-state multi-objective evolutionary algorithm (MOEA) with e-dominance conception is introduced to solve the multi-objective optimal problem at hand. A local search framework using scalar fitness function is proposed to enhance the performance. Experiment results show that the model is reasonable and the algorithms are effective and correct.
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