The Research Of Intelligent Guidance Law Based On Fuzzy Control And Particle Swarm Optimization

International war situation changes rapidly, in future wars, both in defensive oroffensive, precision strike against targets is playing an increasingly important role. Inface of complex operational environment, how to improve the anti-jamming capabilityand the ability to intercept high maneuvering targets of guided weapons becomes a newdirection of guided technology research. Fuzzy control has strong robustness and doesnot rely on the accurate models. Variable universe fuzzy control algorithm can improvecontrol precision while obtaining strong robustness and is widely used in guidedmissiles. Particle swarm optimization is a kind of swarm intelligence algorithm inspiredby the imitation of birds; it is simple, easy for computer implementation and has goodoptimization performance, so the algorithm is also commonly used in guided missiles.In this paper, on the basis of analyzing the guidance models, variable universe fuzzyterminal guidance law, offline particle swarm optimization fuzzy terminal guidance lawand online particle swarm optimization fuzzy terminal guidance law were developed.The main contents of this paper include:Kinematics model and dynamic model between the missile and target wereestablished. A simulation system for guidance algorithm was designed and guidanceperformance evaluation methods were given.On the basis of analyzing the effects of both front and back contraction-expansionfactor on control performance in variable universe fuzzy control, an intelligentcontraction-expansion factor that can achieve input-output coordination was designed.Variable universe fuzzy guidance law was developed according to the variable universefuzzy control theory. The proposed method was simulated with various forms of targetmotions. The simulation result shows good guidance performance.The effect of parameters on optimization performance in PSO algorithm wasanalyzed and a new nonlinear descending inertia factor was designed. Simulations andcomparative studies show better optimization performance of the proposed inertia factor.Considering that in traditional fuzzy guidance laws, the guidance performance wasinfluenced by parameter settings, fuzzy particle swarm optimization offline guidancelaw was developed. Simulation results show good guidance performance of theoptimized guidance law.Online particle swarm fuzzy guidance law that integrates the PSO algorithm andguidance process was developed. The guidance of missiles was synchronized with theevolution of the individual particle swarm; individual particle swarm optimization isequivalent to the guidance for the instantaneous target location, group particle swarmsoptimization is equivalent to the guidance for predicted target position. The evolution results of PSO algorithm were put into the fuzzy controller to generate guidance controlsignals. Analytic fuzzy control controller with intelligent weight factor was used toensure strong robustness and easy implementation for computers. The simulation resultsshow good guidance performance of the proposed online particle swarm fuzzy guidancelaw.