【作者】 赵亮；

【导师】 付兴武；

【作者基本信息】 辽宁工程技术大学 ， 控制理论与控制工程， 2005， 硕士

【摘要】 本文用遗传算法优化模糊控制和神经网络这两种智能控制算法。利用遗传算法的全局收敛性来自动优化设计智能系统中的参数、结构和推理规则等,使智能控制能满足更高的要求。遗传算法优化模糊控制器,控制效果得到改善,系统的稳定性、快速性和准确性得到加强。遗传算法优化神经网络,扩大了神经网络的搜索空间,提高了计算效率,加大了建模的自动化程度。对系统仿真结果比较表明:经过遗传算法优化的智能控制系统在适应性、实时性和鲁棒性得到加强。更多还原

【Abstract】 The paper applies the Genetic Algorithms to optimizing the Fuzzy Control and Neural Network. It uses the global convergence to automatically optimize and design the parameter, structure and deduction principles, etc, in order to accomplish higher demands of the Intelligent Control. Fuzzy Control devices optimized by Genetic Algorithms have improved the control effect, stabilized the system and strengthened the swiftness and accuracy. Neural Network optimized by the Genetic Algorithms has broadened the searching space of the Neural Network, increased the efficiency of calculation and enlarged the automatic extent of constructing models. The simulating results indicate that the Intelligent Control system optimized by Genetic Algorithms has been highly improved in adaptability, timeliness and robustness.更多还原