基于遗传算法的参数在线自调整模糊控制器

来源期刊：中南大学学报(自然科学版)2003年第3期

论文作者：谭冠政 胡生员

文章页码：285 - 289

关键词：遗传算法;在线;自调整;模糊控制器;智能人工腿

Key words：genetic algorithm; on-line; self-tuning; fuzzy controller; intelligent artificial leg

摘    要：提出了一种基于遗传算法优化的自调整模糊控制器的设计方法.该模糊控制器的运行参数自调整公式以系统响应的最大超调量、调整时间及稳态误差为性能指标,利用遗传算法搜索模糊控制器量化因子K_e,K_ec及比例因子Ku公式中相应的最优基准值K_eo,K_eco及K_uo和微调参数K₁,K₂及K₃,设计一个根据系统当前的动态误差e运行参数可在线自调整的模糊控制器,以确保系统的响应具有最优的动态和稳态性能.该控制器已用于控制由作者设计的智能人工腿中的执行电机.计算机仿真结果表明,与运行参数固定的模糊控制器相比,这种自调整模糊控制器具有良好的动态和稳态性能.

Abstract: A self-tuning fuzzy controller is proposed based on the genetic algorithm optimization. By taking the overshoot, regulation time, and steady-state error of system response as the performance indexes and by means of the genetic algorithm, a group of optimal benchmarks K_eo,K_eco, K_uo and a group of tiny adjusting parameters K₁,K₂,K₃ in the formulae of quantization factors K_e,K_ecand scale factorKuare obtained, which are designed as the operational parameters of the self-tuning fuzzy controller. These operational parameters can be automatically adjusted according to the system′s current erroreto ensure that the system response has optimal dynamic and steady-state performances. The controller has been used to control the motor of the intelligent artificial leg designed by the authors. The result of computer simulation shows that it has more excellent control performance than the fuzzy controller whose parameters are fixed in the process of system response.