Collaborative Research: Designs and Theory of State-Constrained Nonlinear Feedback Controls for Delay and Partial Differential Equation Systems

合作研究：时滞和偏微分方程系统的状态约束非线性反馈控制的设计和理论

• 批准号: 1408376
• 负责人: Miroslav Krstic
• 金额: $ 21万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1408376&HistoricalAwards=false
• 关键词: Collaborative; Research; Designs; Theory; State

Collaborative Research: Designs and Theory of State-Constrained Nonlinear Feedback Controls for Delay and Partial Differential Equation SystemsControl systems are used to model many important engineering systems, such as electronics manufacturing processes involving lasers, marine robots that can monitor water pollution, oil drilling and refining, and rehabilitation mechanisms for patients with mobility disorders. However, many of these engineering applications involve input delays, state constraints, and uncertainties that can put them outside the scope of existing controller designs and theory. State constraints occur when the control objectives include avoiding undesirable situations such as collisions with obstacles, while input delays often arise from sensor designs or transport phenomena that make it difficult to measure the current state of the system. Also, it is inherent in many engineering applications that the control mechanisms must be autonomous. One important technique for ensuring autonomy is by using feedback control, which means that the control values must be determined from past values of the state of the system. This project will develop cutting edge feedback control designs and theory that can help address the preceding challenges, and will demonstrate the techniques in real time experiments. One key technique will involve prediction, which provides a way to use past observations from the control system to compute future states of the dynamics and future control values, even when the system involves long input delays or considerable uncertainty. As reflected in the backgrounds of the PIs, the project combines insightful engineering with sophisticated mathematics, with the goal of producing practically useful controls that have rigorous performance guarantees under delays or state constraints. The problems to be addressed are among the most challenging and significant ones in the control engineering community. The project will strive for transformative methods, and will pursue three theoretical strategies. The first will seek generalized Lyapunov function constructions for partial differential equations, which can include extensions of current approach for building strict Lyapunov functions for ordinary differential equations to much more difficult hyperbolic partial differential equation cases. The second strategy will involve representing robust predictive controls as solutions of integral delay equations, and a dual representation in terms of perturbed first-order hyperbolic partial differential equations. Combined with the Lyapunov function constructions, this can provide robust tracking for predictively controlled nonlinear ordinary differential equations and robustness results for the corresponding partial differential equations. The third strategy will use robust forward invariance, which involves specifying the state constraints to facilitate computing maximal allowable perturbation sets to ensure safe operation under uncertainty. The project will be guided by cutting edge engineering applications, to help ensure the practical usefulness of all of the project results. The ordinary differential equation applications will involve neuromuscular electrical stimulation, which is a rehabilitation method that can help restore movement in humans with motor neuron disorders, and the control of a class of autonomous marine robots that are used for bathymetric surveys or to monitor water quality. The partial differential equation applications will involve laser pulse shaping systems that are used in the manufacture of flat panel displays or in photolithography, and a multi-phase flow system that can help mitigate the adverse effects of slugging in oil production.

合作研究：延迟和偏微分方程系统的状态约束非线性反馈控制的设计和理论控制系统用于对许多重要的工程系统进行建模，例如涉及激光的电子制造过程、可以监测水污染的海洋机器人、石油钻探和炼油，以及行动障碍患者的康复机制。然而，许多工程应用涉及输入延迟、状态约束和不确定性，这些可能使它们超出现有控制器设计和理论的范围。当控制目标包括避免与障碍物碰撞等不良情况时，就会出现状态约束，而输入延迟通常由传感器设计或传输现象引起，导致难以测量系统的当前状态。此外，许多工程应用中固有的控制机制必须是自主的。 确保自主性的一项重要技术是使用反馈控制，这意味着控制值必须根据系统状态的过去值来确定。该项目将开发尖端的反馈控制设计和理论，帮助解决上述挑战，并将在实时实验中展示这些技术。一项关键技术涉及预测，它提供了一种使用控制系统过去的观察来计算动态的未来状态和未来控制值的方法，即使系统涉及长输入延迟或相当大的不确定性。正如 PI 的背景所反映的那样，该项目将富有洞察力的工程与复杂的数学相结合，其目标是产生实用的控制，这些控制在延迟或状态约束下具有严格的性能保证。要解决的问题是控制工程界最具挑战性和最重要的问题之一。该项目将努力寻求变革方法，并将追求三种理论策略。第一个将寻求偏微分方程的广义李亚普诺夫函数构造，其中可以包括将用于为常微分方程构造严格李亚普诺夫函数的当前方法扩展到更困难的双曲偏微分方程情况。第二种策略将涉及将鲁棒预测控制表示为积分延迟方程的解，以及扰动一阶双曲偏微分方程的对偶表示。与李亚普诺夫函数构造相结合，这可以为预测控制的非线性常微分方程提供鲁棒跟踪，并为相应的偏微分方程提供鲁棒结果。第三种策略将使用鲁棒的前向不变性，其中涉及指定状态约束以促进计算最大允许扰动集以确保不确定性下的安全操作。该项目将以最先进的工程应用为指导，以帮助确保所有项目成果的实际用途。常微分方程的应用将涉及神经肌肉电刺激，这是一种康复方法，可以帮助患有运动神经元疾病的人类恢复运动，以及用于水深测量或监测水质的一类自主海洋机器人的控制。偏微分方程应用将涉及用于平板显示器制造或光刻的激光脉冲整形系统，以及有助于减轻石油生产中段塞的不利影响的多相流系统。