NASA · NASA-920 · record R0513

Adaptive State-Space Control via Neuromorphic Computing

National Aeronautics and Space Administration · MSFC: Marshall Space Flight Center

Find similar use cases NASA profile

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Science
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Neuromorphic hardware for autonomous control logic adaptation in robotics/aerospace

Expected benefits

This use case addresses the limitations of traditional, fixed-logic control systems by implementing an adaptive state-space model on neuromorphic hardware. By representing a system's states and transitions as a network of spiking neurons and plastic synapses, the governing matrices of the control model are transformed from static constants into dynamic variables that evolve based on real-time sensory input and operational feedback. This enables the system to autonomously learn from its environment, optimize its own control logic, and adapt to unforeseen conditions, creating a foundation for truly intelligent and resilient autonomous systems in fields such as advanced robotics and aerospace.

System outputs

governing matrices of the control model

Technology

AI classification: Agentic AISource: Agentic AI: AI systems that perform tasks or make decisions autonomously with minimal human intervention.
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported