Robust State and Uncertainty Estimation for Unmanned Systems in the Presence of External Uncertainties

存在外部不确定性的无人系统的鲁棒状态和不确定性估计

• 批准号: 1131643
• 负责人: Amit Sanyal
• 金额: $ 27.82万
• 依托单位: New Mexico State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1131643&HistoricalAwards=false
• 关键词: Robust; State; Uncertainty; Estimation; Unmanned

The research objective of this award is to develop a framework for estimation of motion states and uncertain external inputs for feedback control of unmanned vehicles operating in poorly known environments. This framework will specifically address uncertainties due to uncertain external inputs, sensor noise in motion sensors, and time delay in feedback control. A global treatment of vehicle dynamics will make it possible to estimate and control the motion of rapidly maneuvering vehicles in the presence of uncertainties. The estimation schemes are deterministic, but approximate the underlying probability density function describing the uncertainty in the dynamics of the vehicle. A robust control scheme using the estimates of states and uncertain inputs in the presence of bounded time-delay will be formulated to stabilize and control the vehicle. A computational algorithm, based on a discrete-time interpretation of mechanics, will be used to implement the estimation and control schemes in real-time. Deliverables include software implementations of the components of this framework, documentation of research results, and engineering student education. The proposed research will directly impact applications of unmanned systems in poorly known environments. Example applications include space exploration, satellite geodesy, data gathering from tropical storms, underwater pipeline leak detection, and search and rescue missions. Software made possible through this research will offer improvements to the reliability of unmanned systems used in such applications. In particular, results from this research will (1) improve characterization of uncertain inputs affecting the motion of unmanned vehicles, (2) enable the unmanned vehicle to learn and adapt to the uncertainties in its environment, and (3) characterize and exploit time delay in motion control. Graduate and undergraduate engineering students will benefit through classroom instruction and involvement in the research. An educational website will be developed to disseminate research results to students, experts, and the community at large.

该奖项的研究目标是开发一个估计运动状态和不确定外部输入的框架，用于在未知环境中运行的无人驾驶车辆的反馈控制。该框架将专门解决由于不确定的外部输入、运动传感器中的传感器噪声以及反馈控制中的时间延迟而导致的不确定性。对车辆动力学的全局处理将使得在存在不确定性的情况下估计和控制快速机动车辆的运动成为可能。估计方案​​是确定性的，但近似描述车辆动力学不确定性的潜在概率密度函数。将制定在存在有限时延的情况下使用状态估计和不确定输入的鲁棒控制方案来稳定和控制车辆。基于力学的离散时间解释的计算算法将用于实时实施估计和控制方案。可交付成果包括该框架组件的软件实现、研究结果文档以及工程学生教育。拟议的研究将直接影响无人系统在鲜为人知的环境中的应用。示例应用包括太空探索、卫星大地测量、热带风暴数据收集、水下管道泄漏检测以及搜索和救援任务。通过这项研究实现的软件将提高此类应用中使用的无人系统的可靠性。特别是，这项研究的结果将（1）改善影响无人驾驶车辆运动的不确定输入的表征，（2）使无人驾驶车辆能够学习并适应其环境中的不确定性，以及（3）表征和利用时间延迟在运动控制中。工程专业的研究生和本科生将通过课堂教学和参与研究受益。将开发一个教育网站，向学生、专家和整个社区传播研究成果。