Improved Salp Swarm Algorithm And Its Application In Hydraulic Reliability Allocation And Control Optimization

As an emerging intelligent optimization algorithm,salp swarm algorithm has the characteristics of simple principle and few adjustment parameters.In order to further improve the optimization performance of the salp swarm algorithm,this paper will study the population distribution,parameter setting and search mechanism of the algorithm,and use the improved salp swarm algorithm for the system reliability allocation optimization and the PID parameter tuning.The main research contents are as follows:(1)This paper proposes an improved salp swarm algorithm,which adds the strategies of dimension-by-dimension centroid opposition-based learning,random factor and the social learning strategy of particle swarm optimization.First of all,a strategy of dimension-by-dimension centroid opposition-based learning is added to the food source to increase population diversity,reduce inter-dimensional interference,and enhance the ability of the algorithm to jump out of the local optimal solution;secondly,a random factor is added in the follower position update stage to enhance the diversity of follower location updates;finally,the social learning strategy of particle swarm optimization is introduced to give full play to the guiding role of the elite individual in the population,accelerate the trend of salp individuals moving to the food source position through the information sharing mechanism,and improve the optimization accuracy of the algorithm.The simulation results with other intelligent optimization algorithms in 10 benchmark test functions show that the improved salp swarm algorithm has better comprehensive optimization performance.(2)The improved salp swarm algorithm is used to optimize the T-S fault tree reliability allocation model of the bulldozing shovel system of the excavator.The simulation results show that the improved salp swarm algorithm can effectively improve the reliability of the system by reasonably allocating the component failure probability under certain cost constraints.(3)The improved salp swarm algorithm is used to optimize the PID parameter tuning of the valve-controlled asymmetric hydraulic cylinder position servo system.The simulation results show that the improved salp swarm algorithm has better dynamic response characteristics than other intelligent optimization algorithms.In addition,the experimental results on the fault simulation test bench of the electro-hydraulic servo system show that the simulation curve of the system dynamic response is basically consistent with the overall trend of the experimental curve,which verifies the effectiveness of the improved salp swarm algorithm in PID parameter tuning.