Tracking Control of Nonlinear Systems Under Sensing, Computational, and Communication Constraints

传感、计算和通信约束下的非线性系统的跟踪控制

• 批准号: 1232127
• 负责人: Nikhil Chopra
• 金额: $ 32.45万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1232127&HistoricalAwards=false
• 关键词: Tracking; Control; Nonlinear; Systems; Under

Objective: The research objective of this proposal is to investigate control algorithms for resource constrained trajectory tracking in nonlinear systems. Tracking controllers are widely utilized in several applications, for example in robotic systems for manufacturing applications. However, the implementation of these controllers is subjected to several practical constraints that limit overall system performance. In applications, such as robotic systems for industrial automation, these problems have prevented the realization of high precision tracking, thereby stymieing the potential impact of robotic systems. In contrast to time-triggered periodic sampling, in this proposal a Lyapunov function based event-triggered approach is utilized for addressing resource constrained tracking in nonlinear systems.Intellectual Merit: The research deals with design of tracking controllers for nonlinear systems under sensor, computational, and communication constraints. The approach is based on event-triggered controllers for trajectory tracking in nonlinear systems and by co-designing event- triggers and quantizers for nonlinear systems. The research will lead to the development of a hybrid control framework where various resource constraints can be treated in a unified manner. The proposed approach will provide a rigorous solution to the important problem of tracking in robotic systems under sensor constraints, thereby significantly impacting industrial automation.Broader Impact: The understanding of resource constrained trajectory tracking using an event-triggered controller will provide a useful alternative to the classical time-triggered control framework. The proposed research is anticipated to significantly enhance the tracking performance of robotic systems under sensor constraints and render them viable for several emerging manufacturing applications. Graduate students will directly benefit from the proposed research, and it is expected that several undergraduate and graduate students will benefit from the enriched curricula and project work at University of Maryland. High school students from underrepresented groups will be included in the research effort through the University of Maryland?s ESTEEM program.

目的：本提案的研究目的是研究非线性系统中资源受限轨迹跟踪的控制算法。跟踪控制器广泛应用于多种应用中，例如用于制造应用的机器人系统。然而，这些控制器的实现受到一些限制整体系统性能的实际限制。在工业自动化机器人系统等应用中，这些问题阻碍了高精度跟踪的实现，从而阻碍了机器人系统的潜在影响。 与时间触发的周期性采样相比，本提案采用基于李亚普诺夫函数的事件触发方法来解决非线性系统中的资源受限跟踪问题。 智力优点：该研究涉及传感器、计算和通信约束下非线性系统的跟踪控制器的设计。该方法基于用于非线性系统中轨迹跟踪的事件触发控制器，并通过为非线性系统共同设计事件触发器和量化器。 该研究将导致混合控制框架的开发，可以以统一的方式处理各种资源约束。所提出的方法将为传感器约束下机器人系统跟踪的重要问题提供严格的解决方案，从而显着影响工业自动化。更广泛的影响：使用事件触发控制器对资源受限轨迹跟踪的理解将为经典时间触发控制框架提供有用的替代方案。拟议的研究预计将显着增强机器人系统在传感器约束下的跟踪性能，并使它们适用于几种新兴的制造应用。 研究生将直接从拟议的研究中受益，预计一些本科生和研究生将受益于马里兰大学丰富的课程和项目工作。来自代表性不足群体的高中生将通过马里兰大学的 ESTEEM 项目参与研究工作。