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

这个为期两年的项目将把科卡尔博士的概念学习系统COPER扩展到动态系统识别和控制领域。它将重点放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，从而需要对工厂模型进行持续的验证和适应。COPP将推断出一套本地模型，每个模型都足以在适当的控制制度下将工艺维持在安全的运行区域。这将有助于交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.