不完全信息代谢网络广义和混杂系统建模及优化控制

项目名称： 不完全信息代谢网络广义和混杂系统建模及优化控制

项目编号： No.11301081

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 数理科学和化学

项目作者： 叶剑雄

作者单位： 福建师范大学

项目金额： 22万元

中文摘要： 生物代谢系统是由代谢物和代谢反应所构成复杂网络，其信息往往不能完全获悉。本项目拟从以下三方面对一类代谢系统进行研究：第一，针对代谢网络信息不完全和缺少代谢物观测数据等问题，利用结构动力学建模和代谢控制分析等方法，构建广义动力学模型，对系统进行定性分析和预测，并确定关键代谢物和代谢反应；第二，针对关键代谢路径机理不清问题，综合运用经验和机理建模方法，依生物鲁棒性建立并求解一簇非线性混杂动力系统约束的混合优化参量辨识问题；第三，利用不连续微分方程理论、非光滑优化、变分原理和一致逼近理论等数学工具，研究混杂状态空间度量、混杂系统适定性及最优控制等问题。本项目涉及生物数学、控制论、生物化工、系统科学、工程学和计算机科学等领域，是多学科交叉的新兴学科分支。该项研究可为不完全信息的代谢系统研究提供有力的分析和计算方法，为基因工程改造和生化过程控制提供参考，并可丰富广义和混杂系统建模和优化的研究。

中文关键词： 结构动力学；混杂系统；生物鲁棒性；最优控制；数值算法

英文摘要： Metabolic systems can be described by complex networks comprising the chemical reactions of metabolism as well as the regulatory interactions that guide these reactions. It is often the case that the information of metabolic systems cannot be completely known. In this project, we will study a class of metabolic systems in the following three aspects. Firstly, in consideration of the incomplete information and the lack of experimental data, we will use various simplified kinetic modeling frameworks, such as structural kinetic modelling and metabolic control analysis, to construct the generalized kinetic models of the metabolic systems. On this basis, the dynamics of the systems will be analyzed and predicted, and the key metabolites and reactions will be determined. Secondly, in the context of incomplete knowledge of the metabolic mechanisms, we will use both empirical and theoretical modelling techniques to develop a set of hybrid systems for various candidate metabolic systems. Taking the biological robustness as performance index, we will formulate and solve mixed variable identification problems constrained by the set of hybrid systems. Thirdly, by applying the theory of discontinuous systems, nonsmooth optimization, variational principles and consistent approximation, we will study the metric of hybrid-state

英文关键词： Structural kinetic modelling；Hybrid system；Biological robustness；Optimal control；Numerical algorithm