Research On The Application Of Swarm Intelligence Optimization Algorithm In Optimization Design

With the development of technology and society,the demand for optimization is more and more extensive,this also improves the research of optimization methods and algorithms,the development of swarm intelligence optimization algorithm based on bionics and imitating is the fastest,and the particle swarm optimization(PSO)algorithm and the bacterial foraging optimization(BFO)algorithm are the representative algorithms.Compared with the traditional optimization algorithm,the PSO and BFO have many advantages,such as fast solving speed,high accuracy,wide range of application and so on.According to the defects of PSO algorithm for complex optimization problems,based on the basic PSO algorithm as the main part,and then considering the BFO method has the advantages of strong local search ability and the adaptive particle swarm optimization algorithm(APSO)has the characteristics of adaptive weights,this paper puts forward an adaptive particle swarm optimization algorithm based on bacterial foraging(BFPSO),then the algorithm is applied to the design of the center distance of the helical gear of the reducer in the mechanical design,and the three intelligent optimization algorithms of BFO?PSO and BFPSO are compared and analyzed in the simulation optimization design of the automatic flight control system of the aircraft.The major study context in this paper includes those:1.In the theoretical part,this paper first introduces the background and characteristics of swarm intelligence optimization algorithm,and makes a detailed research on the principles,characteristics and operation process of PSO algorithm and BFO algorithm.Then combined with the advantages of PSO algorithm are fast convergence and easy to be precocious,and the BFO algorithm has the advantages of slow convergence and high precision,the steps of core operation with strong local search ability and some strong global search ability of BFO algorithm are mixed in the PSO algorithm,the adaptive weight operator of APSO algorithm is introduced at the same time,BFPSO is proposed.Finally,the convergence,accuracy,reliability and robustness of the three optimization algorithms are tested and compared in detail through several classical test functions,then it is proved that the optimization performance of the BFPSO algorithm has improved significantly than the pre-improved algorithm.2.In the part of application,the BFPSO algorithm is applied to the optimization of gear reducer's center distance,the results of the optimized calculation show that the center distance of the helical gear designed by the BFPSO algorithm is smaller than that of the experience design value and the traditional optimization algorithm in the case of meeting the design requirements.It reflects that the optimization method of BFPSO algorithm proposed in this paper saves the cost of production and improves the design efficiency.The three optimization algorithm are applied to the simulation optimization design of the automatic control system of the aircraft,the three optimization algorithm and the traditional root locus method are compared in the simulation results of vehicle pitch angle and automatic throttle control system,too.The simulation results show that the performance of the BFPSO algorithm is better than that the three optimization algorithm,then the ability of the proposed BFPSO algorithm to solve practical engineering problems is verified effectively.