摘要
黄酒发酵过程中温度对象具有大滞后、非线性和突变性等特点,且生化反应机理不明,难以建立明确的机理模型,采用常规的控制方案难以获得理想的控制效果。针对这一难题,笔者提出了基于蚁群算法优化的模糊控制策略,用蚁群算法对模糊算法的量化因子和比例因子进行优化,提高了模糊控制器的精度和自适应能力。仿真运行结果显示,该算法收敛速度更快,超调量小,能较好地跟踪目标工艺曲线。
During Rice wine fermentation, temperature object shows some characteristics such as large time delay, nonlinear and mutation. Besides, it is difficult to establish a clear mechanism model because of the unknown bio- chemical reaction mechanism. As a result, it is difficult to obtain satisfactory control effect using conventional control schemes. Thus this paper presents a fuzzy control strategy based on ant colony algorithm, which optimizes the quanti- zation factors and scale factor of fuzzy algorithm to improve the accuracy and adaptive capacity of the fuzzy controller. Simulation results show that the the target technology curve can be better tracked using this algorithm due to its faster convergence and small overshoot.
出处
《食品与发酵工业》
CAS
CSCD
北大核心
2013年第10期6-10,共5页
Food and Fermentation Industries
关键词
蚁群算法(ACO)
黄酒发酵
模糊控制
ant colony algorithm (ACO) , rice wine fermentation, fuzzy control~