CRII: SHF: Real-time Approximate-Dynamic-Programming based Neuro-controllers for Dynamic Power Management in Power-Constrained Digital Systems

CRII：SHF：基于实时近似动态编程的神经控制器，用于功率受限数字系统中的动态功率管理

• 批准号: 1464353
• 负责人: Arijit Raychowdhury
• 金额: $ 17.5万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1464353&HistoricalAwards=false
• 关键词: CRII; SHF; Real; time; Approximate

With the Internet of Things (IoT) revolution, self-powered devices with embedded energy harvesters and integrated batteries have become a reality. Such energy sources are prone to wide variations in their voltage, current and power outputs. Simultaneously, load circuits undergo large dynamic ranges through fine-grained spatio-temporal power management, increasing number of power domains, decreasing decoupling between voltage domains and unreliable parasitics. However, the traditional power delivery network (which includes DC-DC converters and voltage regulators), are still designed for the worst-case corner and hence suffer from serious inefficiencies. This results in non-optimal power, performance and energy-efficiency of the overall system. This project proposes a novel and disruptive technology, where a highly dynamic power delivery network in IoT devices is envisioned, which can autonomously adapt, reconfigure and manage itself to meet the varying source and load conditions.The research draws inspiration from recent advances in Approximate Dynamic programming to provide real-time and optimal control of the power delivery network under highly dynamic conditions. Hardware based controllers will be developed to provide real-time optimization of the embedded regulators and DC-DC converters for maximum energy-efficiency under performance constraints. The success of this approach is pivoted on advances in the power delivery network, which will also be explored. Traditional ?static? designs cannot be controlled on the fly. Hence, the second principal theme of the research is to explore ?variable structure control? as a means of realizing an ultra-fast and dynamically reconfigurable power delivery system. This will enable orders of magnitude improvement in energy efficiency across wide dynamic ranges of operation and allow new applications for IoT devices with far reaching societal impact.

借助物联网（IoT）革命，带有嵌入式能量收割机和集成电池的自动设备已成为现实。这样的能源容易产生电压，电流和功率输出的广泛变化。同时，负载电路通过细粒的时空功率管理，增加功率域数量，减少电压域和不可靠的寄生虫之间的去耦。 但是，传统的电力输送网络（包括DC-DC转换器和电压调节器）仍然是为最糟糕的角落而设计的，因此患有严重的效率低下。这会导致整体系统的非最佳功率，性能和能源效率。该项目提出了一种新颖而破坏性的技术，其中设想了IoT设备中高度动态的动力输送网络，该技术可以自主适应，重新配置和设施以满足不同的来源和负载条件。该研究从近似动态计划的最新进展中获得了灵感，以在高度动态的情况下提供对电力交付网络的实时控制和最佳控制。将开发基于硬件的控制器，以提供嵌入式调节器和DC-DC转换器的实时优化，以在性能限制下提供最大的能源效率。这种方法的成功是在电力输送网络中的进步中枢纽的，这也将探讨。传统？静态？设计无法即时控制。因此，研究的第二个主要主题是探索“可变结构控制”吗？ as a means of realizing an ultra-fast and dynamically reconfigurable power delivery system.这将使在广泛的操作范围内的能源效率的数量级提高，并允许针对具有遥远社会影响的物联网设备应用。