A Model of Autonomous System for Scientific Experiments and Spacecraft Control for Deep Space Missions

Abstract

The particularities of autonomous control system for deep space missions are described. A new approach for autonomous control system development is proposed and analyzed in details. Some models are analyzed and compared. The general formal model is based on the theory of communicating sequential processes (CSP). Methods for reconfiguration, verification and trace control are described. The software that is appropriate not only for the spacecraft flight path control but also for autonomous control of scientific apparatus operation and science experiments parameters is described. The software enables onboard scientific apparatus to autonomously detect and respond to science events Science algorithms, including onboard event detection, feature detection, change detection, and unusualness detection, are proposed to be used to analyze science data. Thus detecting features of scientific interest these algorithms are used to downlink only significant science data. These onboard science algorithms are inputs to onboard decision-making Replaner that modify the spacecraft observation plan to capture high value science events. This new observation plan is input for the Task execution subsystem of the Autonomous control system (ACS), able to adjust the plan to succeed despite run-time anomalies and uncertainties, and after it is executed by the ACS, which controls onboard scientific apparatus to enable an autonomous goal-directed exploration and data acquisition to maximize science return.