SGER: Robust Intelligent Automation for Life Science Systems

本项目研究了一种新的基于数据驱动的生命科学自动化规划与控制一体化方案。本研究旨在(I)建立一个架构以促进规划与控制的分析整合，(Ii)采用一个两自由度控制器以实现稳健且智能的生命科学自动化，(Iii)通过模拟测试与评估所获得的结果，(Iv)通过量化分级系统措施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 Permut教授建立联系，为实验研究做准备。预期的好处是(I)先进的非平凡规划算法，以提高生命科学系统设计的安全性和可靠性；(Ii)用于生命科学自动化的先进控制软件；(Iii)为自动化生命科学系统的发展提供科学基础。此外，这项研究还将极大地提高我们对复杂系统的非线性动力学和控制的总体认识，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.