IGA在DEH调节系统参数优化中的应用

The Application of IGA in Parameter Optimization for DEH Control System

遗传算法是模拟自然界生物进化过程和机制对优化问题进行求解。首先概述了遗传算法的基本原理、特点和存在的缺陷,鉴于遗传算法易出现"早熟"现象,对遗传算法进行改进后,将其应用于汽轮机数字电液调节系统的参数优化,并给出了参数优化过程。改进遗传算法提高了算法的全局搜索能力和局部搜索能力。仿真实验表明,改进的算法效果明显优于经典优化算法,能有效克服"早熟"现象、提高算法收敛精度,具有良好的收敛性和寻优能力。

Genetic algorithm（GA） solves the optimization problem by simulating the natural processes and mechanisms of biological evolution.The principle,character and flaw of genetic algorithm are firstly overviewed in the article.In view of genetic algorithm prone to ＂premature＂ phenomenon,this paper improves genetic algorithm.Then,the improved genetic algorithm is used for parameter optimization of turbine Digital Electrical Hydraulic（DEH） control system,and the process of parameter optimization is presented.The improved genetic algorithm increases the global and local search capability.The simulation and experimental results show that the improved algorithm is superior to classical optimization algorithm,can overcome ＂premature＂ phenomena and improve the convergence precision,which demonstrates the improved genetic algorithm has better performance of convergence and fine ability of optimization.