基于遗传算法的自学习模糊逻辑系统  

Self-learning Fuzzy Logic System Based on Genetic Algorithm

作　　者：王宏伦[1] 吕庆风 佟明安[2] 

机构地区：[1]南京航空航天大学无人机研究所,210016 [2]西北工业大学电子工程系

出　　处：《控制与决策》2000年第6期658-661,共4页Control and Decision

摘　　要：利用遗传算法实现模糊逻辑系统的自学习 ,提出了遗传算法和模糊逻辑系统的结合方式 ,并针对模糊逻辑系统的特点 ,提出了初始种群的生成方法 ,较大地提高了遗传模糊逻辑系统的自学习性能。仿真结果表明 ,该系统对复杂的非线性系统具有较好的学习效果。Genetic algorithm is introduced to the self learning procedure of fuzzy logic systems. The structure of fuzzy systems based on genetic algorithm is presented, and the relevant real coded genetic operators such as duplication, crossover and mutation are defined. Through a modification to normal population initializing method, the redundant parts of search space are reduced, the convergence speed is increased. Simulation results show that the genetic fuzzy logic systems can study well from nonlinear systems.

关 键 词：遗传算法 自学习 模糊逻辑系统 系统辨识 

分 类 号：O231.3[理学—运筹学与控制论]