Fuzzy logical guidance based on particle swarm optimized parameters

Fuzzy logic control guidance (FLCG) law has been proved to be effective and robust, but the parameters of the fuzzy logical controller are usually difficult to determine and have great influence on the pursuit and intercept performance. In this paper, an optimal fuzzy logic control guidance (OFLCG) law is designed by applying particle swarm optimization method to optimize parameters of fuzzy logic controller. The objective is to improve the performance of FLCG by possibly minimizing the cost function, which is properly designed as a weight sum of pursuit time and energy consumptions. The parameters selected to be optimized are width of the membership functions, number of fuzzy partitions, and defuzzification method. Simulation results show that the intercept performance of the designed guidance law is better than that of FLCG and proportional navigation guidance (PNG) law.