MUMBAI, India, Aug. 24 -- Intellectual Property India has published a patent application (202641097776 A) filed by Sns Academy on August 13, 2026, for Autonomous Phase-Space-Based Predictive Stability And Self-Correction System For Spacecraft Using Non-Linear Dynamical Modeling.
Inventors include Sarvesh D P; Dr. A. Saranya; Mrs. Ganga Devi R; and Pranesh J.
The application for the patent was published on August 21, 2026, under issue no. 34/2026.
Abstract: The present invention discloses an Artificial Intelligence (AI)-driven autonomous spacecraft stability prediction and self-correction framework that integrates phase- space evolution analysis, nonlinear dynamical modeling, chaos-inspired instability detection, and intelligent decision-making to enhance spacecraft operational reliability. The proposed system continuously acquires multidimensional telemetry from a plurality of spacecraft subsystems, including but not limited to attitude determination, propulsion, thermal management, power distribution, communication, and onboard computing systems. The acquired telemetry is processed to generate a unified multidimensional state vector representing the instantaneous operational condition of the spacecraft. The generated state vector is mapped into a phase-space representation, wherein the temporal evolution of the spacecraft state is continuously monitored to identify trajectory divergence, nonlinear oscillatory behavior, and early indicators of instability. The invention further incorporates nonlinear dynamical analysis and chaos-inspired stability indicators to recognize abnormal system evolution before conventional threshold-based fault detection mechanisms are activated. Upon detection of potential instability, an Agentic Artificial Intelligence Decision Engine autonomously evaluates the evolving system dynamics and determines appropriate corrective control strategies. The generated control commands are transmitted to the spacecraft control subsystem to regulate attitude, power allocation, thermal conditions, propulsion, or other operational parameters, thereby maintaining overall spacecraft stability through a closed-loop feedback mechanism. Unlike conventional reactive monitoring systems that respond only after predefined operational limits have been exceeded, the proposed framework is configured to predict instability based on system evolution, enabling proactive intervention before critical failures occur. By integrating unified state representation, phase-space trajectory analysis, nonlinear dynamic modeling, autonomous AI-based reasoning, and adaptive feedback control within a single framework, the invention provides a scalable approach for improving spacecraft autonomy, operational resilience, and long- duration mission reliability. The disclosed framework is applicable to satellites, deep-space exploration vehicles, planetary probes, autonomous orbital platforms, and future intelligent spacecraft systems requiring predictive health management and self-corrective operational capabilities.
Disclaimer: Curated by HT Syndication.
