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

这笔拨款将资助可再生能源发电系统的研究，如风力涡轮机和风筝，在广泛的环境条件下实现最佳运行，从而促进科学进步，促进国家繁荣。环境变化给能量收集系统带来了操作上的挑战，可以通过实时可重构性来解决：同时，动态地改变物理机制（工厂）和系统控制，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装置和控制参数。然而，由于修改工厂参数和控制参数所需的时间尺度和努力存在重大差异，因此不存在针对环境可变性和不确定性的实时操作方法。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，该框架可以解释实时操作中的这些差异，并将进一步量化计算需求，使实时可重构性值得额外的成本和复杂性。该项目将利用国际能源机构空中风能任务的参与，组织年度研讨会，讨论可重构能源收集系统模型的使用以及该项目创建的开源软件工具。通过在现有的K-12课程中实施“风筝物理学”研讨会，将促进学生对可再生能源技术的参与。本研究旨在为实时植物可重构性开发后退地平线协同设计框架的基础，同时也解决了植物和控制参数之间的基本区别。它通过融合嵌套协同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)考虑两个层次的经济（而不是跟踪）公式而产生的关键知识差距，（ii）纳入可追溯性的替代模型，以及（iii）考虑环境随机性。具体来说，我们将研究一种多速率架构，即上层工厂优化使用低阶代理模型来近似捕获下层控制系统优化的预期行为。一个相互关联的误差系统模型和小增益框架将用于解决在不同环境参数变化速率下的收敛和效率问题。最后，递归高斯过程建模将用于表征环境不确定性，同时将确定性目标函数重新表述为统计函数，引入机会约束，并在概率意义上评估理论性质。该框架将通过在具有实时变形能力的能量收集水下风筝上进行广泛的模拟和规模实验验证活动来评估。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.