EHS: Hybrid Estimation and Control with Bounded Probabilities

Mark E. Campbell，康奈尔大学，有界概率的混合估计和控制这个项目正在开发一种新的混合估计方法，用于混合系统研究中设想的应用。开发了三个领域的混合估计研究，使用已知实例和实时测试平台进行综合评估过程。首先，建立了一个有界概率混合估计器，其中并行实现了多个连续估计器，每个估计器具有不同的概率水平。系统（用户或混合控制器）可以将估计器切换到所需的概率水平。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联系起来。其次，将混合估计与控制和规划联系起来，重点研究混合动力汽车的切换控制，包括有界模型不确定性的过渡。第三，开发了混合估计器的计算基础结构，包括实时实现。理论工作首先通过简单的已知示例进行系统验证，然后是可以进行数值评估的更复杂的示例，最终在康奈尔测试台上进行实时嵌入式混合系统评估。康奈尔SeaScan无人机测试平台是一套多达四架小型无人机，以及一个类似的基于实验室的硬件在环测试平台。在夏季，本科生与博士生和博士后合作，努力过渡和实验验证这些技术。这项工作有望通过在现实环境中实现一般类型的混合理论（如控制和规划）来推进混合系统理论。混合估计器允许“拨通”一定程度的概率（比如风险）。当车辆控制和规划被用作动机时，混合估计器被开发用于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.