【作者】 肖杰；

【导师】 史仲平；

【作者基本信息】 江南大学 ， 生物化工， 2008， 硕士

【摘要】 本论文以谷氨酸发酵为研究对象,在实验的基础上运用数学建模和计算机仿真对其发酵过程的优化和控制进行了研究。在利用谷氨酸棒杆菌S9114进行谷氨酸发酵过程中,通过代谢网络模型计算发现,控制不同的RQ(呼吸商)水平与代谢通量在谷氨酸、乳酸和TCA循环三者之间的分配有密切的关系。因此,确立了基于RQ在线测量的平衡代谢控制策略,以达到调节TCA循环代谢通量,从而实现提高谷氨酸浓度、抑制代谢产物的目标。通过分析RQ对于搅拌速度大辐阶跃式变化的时间响应,我们发现对RQ的控制可以通过调节转速来实现。为此我们通过转速的PI反馈控制器来实现对RQ的控制,从而使TCA循环的代谢通量保持在一个合适的水平以实现谷氨酸发酵过程的优化,但是,由于RQ和搅拌转速之间存在着响应滞后,RQ的控制性能还有待进一步提高。为此,在取得基本数据后,在RQ与搅拌转速有响应关系的前提下,建立了搅拌转速与RQ之间的动力学模型,并用Matlab软件Simplex(单纯型法)法确定了方程参数。由于在发酵实验中传统的PI反馈控制对RQ的控制性能较差,因此我们建立了一个基于自回归移动平均模型的在线自适应PI反馈控制器,试图对发酵过程控制中的反馈控制器的控制参数进行实时调节,以适应发酵过程时变性特征。通过计算机仿真发现,在不考虑滞后时,无论模型结构是否发生变化,自适应PI控制比传统的PI控制的控制性能要好,并有不需要进行人工整定PI控制参数的优势。更多还原

【Abstract】 Glutamate fermentation was regarded as research object in the paper, the control and optimization of its fermentation process were studied via mathematical modeling and computer simulation on the basis of experimental research. During glutamate fermentation using Corynebacterium glutamicum S9114, it was found that respiratory quotient (RQ) control was closely related to the distribution of metabolic flux among glutamic acid, lactate and tricarboxylic acid cycle through metabolic reaction network model. To improve the concentration of glutamate and inhibit the metabolic byproduts, the“balanced metabolic control”(BMC) strategy based on the RQ on-line measurement for regulating metabolic flux of tricarboxylic acid cycle was established. According to the study of the time respondence of RQ to large step changes in agitation rate, we found that the RQ control could be achieved by regulating the agitation rate of fermenter. Thus, a PI feedback controller was used to control RQ, so that the metabolic flux of TCA cycle maintained at a suitable level to achieve glutamic acid fermentation process optimization. Because the delay between the RQ with the agitation rate of fermentor, how to improve the control performance must be study. Dynamic model between the agitation rate of fermentor and RQ was constructed applying differential equations on the premise of obtaining basic data and the equation parameter was determinated based on the MATLAB software,using the simplex search method. It was found that the control performance was unsatisfactory by ordinary PI feedback control. So an on-line self-adaptive PI controller based on the auto-regression and moving average model was established, which could real-time adjust PI parameters of the fermentation process. Self-adaptive PI control could improve the performance of RQ control compare to ordinary PI control through computer simulation.更多还原