Towards Control of Time-Varying Systems: Qualitative and Quantitative Modeling

这个为期两年的项目将把Kokar博士的概念学习系统COPER扩展到动态系统识别和控制领域。它将集中在过程以随机间隔改变其目标和特征的领域中的模型识别，需要持续验证和适应工厂模型。COPER将推断出一组局部模型，每个模型都足以在其适当的控制制度下将过程维持在安全的操作区域。这应该有助于在切换环境中的智能控制理论。

This two-year project will extend Dr. Kokar's concept-learning system, COPER, to the domain of dynamic-system identification and control. It will focus on model identification in domains where processes change their goals and characteristics at random intervals, necessitating continuous validation and adaptation of the plant model. COPER will infer a set of local models, each adequate to maintain the process in a safe operating region during its appropriate control regime. This should contribute to the theory of intelligent control within switching environments.