Handling Constraints and Uncertainty in Chemical Process Operation Using Nonlinear Model Predictive Control

使用非线性模型预测控制处理化工过程操作中的约束和不确定性

• 批准号: RGPIN-2016-05391
• 负责人: Mhaskar, Prashant
• 金额: $ 2.77万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637832
• 关键词: Handling; Constraints; Uncertainty; Chemical; Process

Control of chemical processes has long grappled with challenges such as the presence of constraints on the inputs (valves and pumps limited in capacity), nonlinearity and uncertainty (disturbances or plant model mismatch). While there has been significant research in control theory over the last several decades, the availability of modern sensing and computational capabilities have opened up the possibilities of control designs that were in the past computationally intractable.

化学过程的控制长期以来一直在努力应对各种挑战，例如对输入的约束（阀门和泵的容量有限），非线性和不确定性（干扰或工厂模型不匹配）。虽然在过去的几十年里，控制理论已经有了重要的研究，但现代传感和计算能力的可用性已经开辟了控制设计的可能性，而这些控制设计在过去是计算上难以处理的。