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

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

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.