A dynamic genetic algorithm based on particle filter for UCAV formation control

Formation control problem is an important issue in formation flying of unmanned combat aerial vehicles (UCAVs). A dynamic genetic algorithm based on particle filter (PFDGA)was proposed to solve this dynamic optimal control problem. Within this algorithm, the genetic algorithm (GA) and the particle filter (PF) are properly combined together. The GA provides observation of global optimum for the PF and the PF guide the search of the GA. Experimental results show PFDGA performs better in compare with random immigration GA (RIGA) and the formation control problem is effectively solved by PFDGA.