Real-Time Control Co-Design for Reconfigurable Energy-Harvesting Systems

这笔赠款将用于研究，使风力涡轮机和风筝等可再生能源发电系统能够在各种环境条件下以最佳方式运行，从而促进科学进步和国家繁荣。环境的多变性给能源收集系统带来了操作上的挑战，这可以通过实时可重构性来解决：同时对物理机制(工厂)和系统控制进行动态更改，以确保持续的高效率。离线设计方法可以在固定条件下选择最优的对象和控制参数。然而，由于分别修改工厂参数和控制参数所需的时间尺度和努力的关键差异，因此不存在用于响应环境变异性和不确定性的实时操作的这种方法。该项目将通过开发一种创新的算法框架来填补这一知识空白，该框架将解释实时操作中的这种差异，并将进一步量化计算要求，使实时可重构性具有额外的成本和复杂性。国际和平研究所将利用与国际能源署航空风能任务的接触，组织关于使用可重新配置的能源收集系统模型和在该项目中创建的开源软件工具的年度讲习班。学生对可再生能源技术的参与将通过在现有的K-12课程中实施“风筝物理”工作坊来促进。这项研究的目的是为实时工厂可重构性建立一个滚动范围合作设计框架的基础，同时也解决了工厂和控制参数之间的根本区别。它通过融合嵌套联合设计和多速率分层模型预测控制的概念来实现这一结果，解决了由于同时需要(I)考虑在分层结构的两个级别上的经济(而不是跟踪)公式，(Ii)纳入可处理性的代理模型，以及(Iii)考虑环境随机性而产生的关键知识空白。具体地说，将研究多速率体系结构，由此上级对象优化使用低阶代理模型来近似捕获下级控制系统优化的预期行为。将使用一个相互关联的误差系统模型和小增益框架来解决在不同环境参数变化率下的收敛和效率问题。最后，将使用递归高斯过程建模来表征环境不确定性，同时将确定性目标函数重新表述为统计目标函数，引入机会约束，并从概率意义上评估理论性质。该框架将通过对具有实时变形能力的能量收集水下风筝的广泛模拟和大规模实验验证活动进行评估。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This grant will fund research that enables renewable energy generation systems, such as wind turbines and kites, to operate optimally over a wide range of environmental conditions, thereby promoting the progress of science and advancing the national prosperity. Environmental variability poses operational challenges for energy-harvesting systems that can be addressed using real-time reconfigurability: simultaneous, on-the-fly changes to both the physical mechanism (plant) and the system control to ensure sustained high efficiency. Offline design methodologies can select optimal plant and control parameters for fixed conditions. No such methodology exists, however, for real-time operation in response to environmental variability and uncertainty, due to critical differences in time scale and effort required to modify plant parameters and control parameters, respectively. This project will fill this knowledge gap by developing an innovative algorithmic framework that accounts for such differences in real-time operation and will further quantify the computational requirements to make real-time reconfigurability worth additional costs and complexity. The PI will leverage engagement with the International Energy Agency Task on Airborne Wind Energy to organize annual workshops on the use of reconfigurable energy-harvesting-system models and open-source software tools created in this project. Student engagement with renewable energy technology will be promoted by implementing a “Physics of Kites” workshop in existing K-12 programming.This research aims to develop the foundations of a receding horizon co-design framework for real-time plant reconfigurability while also addressing fundamental distinctions between plant and control parameters. It accomplishes this outcome by fusing notions from nested co-design and multi-rate hierarchical model predictive control, addressing critical knowledge gaps that arise due to the simultaneous need to (i) consider an economic (rather than tracking) formulation at both levels of the hierarchy, (ii) incorporate surrogate models for tractability, and (iii) consider environmental stochasticity. Specifically, a multi-rate architecture will be investigated whereby a low-order surrogate model is used by the upper-level plant optimization to approximately capture the anticipated behavior of the lower-level control system optimization. An interconnected error system model and small gain framework will be used to address questions of convergence and efficiency under different rates of environmental parameter variation. Finally, recursive Gaussian Process modeling will be used to characterize environmental uncertainty, while reformulating deterministic objective functions into statistical ones, introducing chance constraints, and assessing theoretical properties in a probabilistic sense. The framework will be evaluated through an extensive simulation and scaled experimental validation campaign on an energy-harvesting underwater kite with real-time morphing capability.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.