基于免疫遗传算法优化的模糊控制方法及其应用

在模糊控制器的设计过程中，为了使模糊控制器的性能达到全局优化，应用免疫遗传算法对模糊控制器参数进行优化设计；在综合考虑各种参数对控制器性能影响的基础上，给出了一种全面优化隶属度函数、比例因子和量化因子的优化方法；利用了免疫算法能保持个体的多样性和能对学习过程进行引导的特点，对模糊控制器的多个参数同时进行优化，从而显著提高了系统的收敛性、稳定性。应用该方法对数控铣削加工过程的模糊控制器的设计进行了仿真，并与其他方法进行比较和控制实例的验证，表明了该基于免疫遗传算法优化的模糊器能获得更优良的控制性能。

Optimization of fuzzy logic control based on immune-GA and application in CNC machining

The immune-genetic algorithm(GA) was used to optimize the fuzzy logic control.The method of optimizing membership functions,scale factors and quality factors was presented;the converge speed and stability were improved because the diversity was maintained and the learning process was led by immune-GA.The simulation and application in computer numerical control(CNC) machine process with this method show that the proposed method has better performance compared with other methods.