摘要
发酵过程的自身复杂性以及菌体生长的不可逆性导致在单批发酵过程中模型的参数变化较大,本文在丝状菌体生长的产物结构模型基础上,利用检测到的数据对发酵过程模型中的参数分时段进行修正。通过灵敏度分析得到对状态变量影响较大的参数,采用经繁殖操作改进的粒子群算法对参数进行寻优修正。实验证明,基于分时段参数修正的发酵模型能适应单批发酵过程中的参数变化,具有精度高、修正速度快等优点。
Due to the complexity of fermentation process and the non-reversibility of microorganism growth, the model parameters of batch fermentation process vary largely. Using the structure model of hyphomycetoma growth, a time-segment parameter adjustment approach was proposed to adapt to the change of parameters throughout the fermentation process. The major influencing factors were firstly selected from many parameters with sensitivity analysis method and then were adjusted using particle swarm optimization method improved by breeding manipulation. Experiment shows that this method features high precision, rapid adjusting speed and suits the parameter changes in batch fermentation process.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2006年第12期1600-1604,共5页
Chinese Journal of Scientific Instrument
基金
国家自然科学基金(60374003)
973计划子课题(2002CB312200)
教育部及辽宁省流程工业综合自动化重点实验室开放课题基金(PAL200509
PAL200511)资助项目
关键词
发酵
分时段
参数修正
结构模型
灵敏度分析
粒子群优化算法
fermentation time-segment parameter adjustment structure model sensitivity analysis particle swarm optimization
