Research on Multistrategy Improved Evolutionary Sparrow Search Algorithm and its Application

To address the problem of sparrow search algorithm (SSA) has poor global ability, weak local development and easily falls into optimal solution, a multi-strategy improved evolutionary (MSSA) is proposed. The introduction tent chaotic map improves diversity initialization population, accelerates convergence, convergence accuracy. Endow finders with random ability to coordinate balance between development. discover dangerous individuals, mutation evolution operation completed, greedy strategy combined improve processing for solutions make full use each individual. Six benchmark functions were used comprehensively verify feasibility proposed based on four aspects: optimization robustness, trajectory. These results indicate that superior. Finally, through comparison analysis parameter identification control strategies two servo systems in practical application, one hand, advantages engineering applications are illustrated. In addition, fuzzy PID MSSA By adding step, sinusoidal, triangular wave disturbance signals, simulation experiments show can significantly dynamic steady performance system.