A Parallel AI Framework for Autonomous Microgrid Control in Aerospace Systems Application Potential for NASA and the Canadian Space Agency for Deep Neural Control Module (DNCM)
Adnan Haider Zaidi · International Journal of Engineering Research and Applications · 2025
Recent advancements in space exploration platforms, such as NASA’s Artemis lunar base program and the Canadian Space Agency’s Gateway power systems, demand resilient, autonomous, and intelligent energy control solutions. These systems operate in dynamic, resource-constrained, and fault-prone environments where traditional SCADA or PLC-based controls lack adaptability and predictive capability. This paper presents HIRACLE—Hybrid Intelligent Resilient Adaptive Control and Learning Engine—a novel parallel AI framework specifically designed for microgrid systems in extraterrestrial habitats and highaltitude UAV missions. HIRACLE features a modular, edge-deployable architecture combining transformer-based forecasting, deep reinforcement learning, spiking neural fault detection, and graph-based rerouting, all supported by meta-learning for continuous mission adaptation. The software implementation utilizes containerized deep learning models (TensorFlow/PyTorch) optimized for edge inference using platforms such as NVIDIA Jetson AGX Orin and Xilinx Versal AI Edge SoCs. These models are deployed as distributed agents capable of parallel operation via high-speed buses (CAN-FD, SpaceWire), ensuring real-time coordination across subsystems. Fault classification, ripple anticipation, load optimization, and health-aware scheduling are executed concurrently without centralized computation. On the hardware front, HIRACLE integrates reconfigurable logic (FPGAs), neuromorphic processors (Intel Loihi 2), SiC-based power conditioning units, and secure telemetry interfaces into a ruggedized control environment. A new chip-level proposal—HIRACLE-IC—is introduced, consolidating all AI, logic, sensing, and secure communication into a single embedded platform ready for deployment in lunar, Martian, or stratospheric UAV energy systems. This approach not only surpasses existing state-of-the-art autonomous energy controls but also positions HIRACLE as a foundational control paradigm for future NASA and CSA missions requiring scalable, intelligent, and mission-adaptive microgrid autonomy.