Enhancing the Efficiency in Checking Constraints Satisfaction when Planning Ground-based and Space Experiments, Using an Alternative Problem

TL;DR

This paper introduces a formal automata-based approach to improve the efficiency of constraint satisfaction checks in planning space and ground experiments, demonstrating real-time optimization benefits.

Contribution

It proposes a novel automata-theoretic formulation for situational analysis and optimization in experiment planning, enhancing computational efficiency.

Findings

Improved efficiency in constraint satisfaction checking.

Successful application to real-time photometric system control.

Demonstrated optimization in complex environment models.

Abstract

The situational analysis lies in the basis of space and ground-based experiment planning. It is connected with the use of complex computation models of environment and with verification of the restricting conditions, due to the character of the conducted experiments and the solved scientific tasks. The present work proposes a formulation of the situational analysis on the basis of the finite abstract automata theory. On this basis, optimization of the situational analysis is suggested by formal schemes for adaptation to the conditions of the model environment. The efficiency enhancement is illustrated by results from the application of the proposed real-time optimization for photometric system control.