Combined Guidance Law Model Based on Particle Swarm Optimization
The proportional guidance law is a classical guidance method that offers significant benefits,such as excellent ballis-tics and minimal data requirements. However,this method faces challenges in meeting requirements related to maneuvering tar-gets and inter-bomb coordination time constraints,due to its ballistic characteristics. Particle swarm optimization ( PSO) is a widely used optimization strategy that can search for parameter-optimal solutions within constraints. This strategy follows estab-lished design steps. In this article,the proportional guidance law is enhanced by the correction of strike angle and strike time,resulting in a combined guidance law. By using constraint functions for striking angle,overload,off-target amount,and striking time,the PSO technique is employed to optimize the parameters of the combined guidance law,thereby achieving an effective strike. The experimental results show that this guidance law design and the intelligent parameter selection strategy can enable a missile to meet relevant requirements with a strike time error of less than 1％. Compared to traditional empirical parameter se-lection methods,intelligent parameter selection yields better ballistic characteristics and reduces the effect of target maneuve-ring.
combined guidance lawparticle swarm optimizationproportional guidance lawnavigation guidancesliding mode control
万方数据
维普
