Functional State Modelling of Biotechnological Processes and Their High Quality Control in the Class of Variable Structure Systems

变结构系统类生物技术过程的功能状态建模及其高质量控制

• 批准号: 5422390
• 负责人: Professor Dr. Bernd Hitzmann
• 金额: --
• 依托单位: Deptartment of Modelling and Optimization of Bioprocess Systems
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2003
• 资助国家: 德国
• 起止时间: 2002-12-31 至 2005-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5422390?language=en
• 关键词: Functional; State; Modelling; Biotechnological; Processes

In biotechnology there are still high requirements of efficient automation systems and algorithms. Conventional control algorithms, like PI or PID, cannot provide optimum performance over the whole operating range of a fermentation process due to its inherent nonlinear and time- variant properties. The complexity of the fed-batch processes and lack of adequate models limit the application of conventional controllers and require several tuning adjustments. Moreover, a flow injection analysis (FIA) system has been developed, which can measure glucose without any probing system and ensures a fast measurment of glucose. The common modelling approach is to synthesise one global process model but there is a big disadvantage, namely complex model structure and big number of model parameters, which complicate the model simulation and parameter estimation. One alternative, but not so wellstudied, way is the implementation of functional state modelling approach. It is a new concept which helps in monitoring and control of complex processes such as bioprocesses. The main advantage of functional state modelling is that the parameters of each local model can be separately estimated from other local models. The implementation of functional state modelling approach allows the elaboration and tuning of simpel control algorithms for each state, which will be consecutively integrated into variable structure control system. So, high control algorithms, namely variable structure systems, variable structure systems with boundary layer and fuzzy variable structure systems are elaborated to take into account the peculiarities of FIA and to overcome some of disadvantages of conventional control algorithms. For fed-batch cultivations of Escherichia coli and Saccharomyces cerevisiae these high control algorithms allow to control the substrate (glucose) concentration at a low set point so that undesirable byproducts like acetate or ethanol will not be produced during the cultivation and the simulations made presents the efficiency ot these algorithms. One of the goals of the project will be implementation of elaborated high control algorithms for real fermentations of E. coli and S. cerevisiae. The application of presented high control algorithms for real process should be made to establish their applicability and to compare with re sults achieved with working extended Kalman filter. The further required improvements, both in modelling and control, will be done to receive better system performance.

生物技术对高效的自动化系统和算法仍有很高的要求。传统的控制算法，如PI或PID，由于其固有的非线性和时变特性，无法在发酵过程的整个操作范围内提供最佳性能。进料批过程的复杂性和缺乏足够的模型限制了传统控制器的应用，并且需要多次调整。此外，还开发了一种流动注射分析（FIA）系统，该系统可以在没有探针系统的情况下测量葡萄糖，并保证了葡萄糖的快速测量。常用的建模方法是综合一个全局过程模型，但其缺点是模型结构复杂，模型参数多，使模型仿真和参数估计复杂化。另一种方法是实现功能状态建模方法，但没有得到很好的研究。这是一个新的概念，有助于监测和控制复杂的过程，如生物过程。函数状态建模的主要优点是每个局部模型的参数可以从其他局部模型中单独估计出来。功能状态建模方法的实现允许对每个状态进行简单的控制算法的细化和调整，这些算法将连续集成到变结构控制系统中。因此，为了克服传统控制算法的一些缺点，本文阐述了高级控制算法，即变结构系统、带边界层的变结构系统和模糊变结构系统。对于大肠杆菌和酿酒酵母的补料分批培养，这些高控制算法允许将底物（葡萄糖）浓度控制在一个低设定点，以便在培养过程中不会产生不需要的副产物，如醋酸盐或乙醇，所做的模拟显示了这些算法的效率。该项目的目标之一将是为大肠杆菌和酿酒杆菌的实际发酵实施精心设计的高控制算法。本文提出的高级控制算法应应用于实际过程，以确定其适用性，并与工作扩展卡尔曼滤波器的结果进行比较。在建模和控制方面需要进一步的改进，以获得更好的系统性能。