SGER: Robust Intelligent Automation for Life Science Systems

本项目研究一种新的集成数据驱动的生命科学自动化规划和控制方案。本文的研究目的是（i）建立一个便于规划和控制分析集成的框架，（ii）采用一个二自由度控制器来实现生命科学自动化的鲁棒性和智能性，（iii）通过仿真测试和评估所获得的结果，（iv）设计一个具有高度鲁棒性和智能性的系统来实现生命科学自动化。（iv）通过定量分级系统测量来评估所提出的葡萄糖控制器，以及（v）与华盛顿大学医学院的Alan Permutt教授建立联系以准备实验研究。预期的好处是：（i）一个先进的非平凡的规划算法，以提高生命科学系统的设计的安全性和可靠性，（ii）一个先进的控制软件的生命科学自动化，和（iii）自动化生命科学系统的发展的科学基础。此外，这项研究将大大提高我们对非线性动力学和复杂系统控制的一般理解，并将对生物工程领域的研究和发展产生特定的影响。

This project studies a new integrated data-driven planning and control scheme for life science automation. Particular attention is paid for the objective of designing a highly robust and intelligent system to achieve the safety and reliability.The research here intends to (i) create a framework for facilitating analytical integration of planning and control, (ii) adopt a two degree-of-freedom controller for robust and intelligent life science automation, (iii) test and evaluate of the obtained results via simulation, (iv) evaluate the proposed glucose controller by a quantitative grading system measure, and (v) establish contact with Professor Alan Permutt at Washington University Medical School to prepare for experimental studies. The expected benefits are (i) an advanced nontrivial planning algorithm to improve safety and reliability of the design of life science system, (ii) an advanced control software for life science automation, and (iii) a science base for the development of automated life science systems. Additionally this research will significantly enhance our general understanding about nonlinear dynamics and control of a complex system and will have a specific impact on the bio-engineering fields in terms of their research and development.