EHS: Hybrid Estimation and Control with Bounded Probabilities

Mark E.坎贝尔，康奈尔大学，混合估计和控制与有界概率这个项目正在开发一种新的方法，混合估计的应用设想在混合系统的研究。三个领域的混合估计研究开发，与集成的评价过程中使用已知的例子和真实的时间测试床。首先，开发了一种有界概率混合估计器，其中多个连续估计器，每个估计器在不同的概率水平上，并行实现。系统（用户或混合控制器）可以将估计器切换到期望的概率水平。水平集用于定义每个概率水平，并将其与原始概率密度函数相关联。其次，混合估计和控制和规划之间的连接，切换混合动力汽车控制，包括有界模型不确定性的过渡的具体重点。第三，计算基础设施的混合估计，包括真实的时间实现。理论工作是系统地验证使用简单的，已知的例子，其次是更复杂的例子，可以进行数值评估，最终一个真实的时间，嵌入式混合动力系统的康奈尔测试平台上的评估。 康奈尔海洋扫描无人机试验台是一套多达四个小型无人机，和一个类似的基于实验室的硬件在环试验台。在暑假期间，本科生与博士生和博士后合作，努力通过实验转换和验证技术。这项工作有望通过使混合理论（如控制和规划）的一般类在现实环境中实现来推进混合系统理论。混合估计器允许概率水平（如风险）被“拨高”。“虽然车辆控制和规划被用作动机，但混合估计器的开发是为了允许从生物到空中交通管制系统的混合系统的一般实施。

Mark E. Campbell, Cornell University, Hybird Estimation and Control with Bounded ProbabilitiesThis project is developing a novel approach for hybrid estimation for applications envisioned in hybrid systems research. Three areas of hybrid estimation research are developed, with an integrated evaluation process using known examples and real time testbeds. First, a bounded probability hybrid estimator is developed, where multiple continuous estimators, each at a different level of probability, are implemented in parallel. The system (user or hybrid controller) can switch estimators to the level of probability desired. Level sets are used to define each probability level, and relate it back to the original probability density function. Second, connections between hybrid estimation and control and planning are made, with a specific focus on switching hybrid vehicle control, including transition of bounded model uncertainties. Third, a computational infrastructure for the hybrid estimators is developed, including real time implementations. Theoretical work is systematically validated using simple, known examples first, followed by more complex examples that can be numerically evaluated, to ultimately a real time, embedded hybrid systems evaluation on a Cornell testbed. The Cornell SeaScan UAV testbed is a suite of up to four small UAV's, and a similar lab-based, hardware-in-the-loop testbed. During the summers, undergraduate students are teamed with PhD students and post-docs in an effort to transition and verify the technologies experimentally.This work is expected to advance hybrid systems theory by enabling a general class of hybrid theory (such as control and planning) to be implemented in a realistic setting. The hybrid estimator allows a level of probability (such as risk) to be "dialed up." While vehicle control and planning are used as motivation, the hybrid estimator is developed to allow general implementation for hybrid systems, from biological to air traffic control systems.