Distributed Multi-Objective Optimization Control Strategy and Real-Time Assessment of Uncertainty Risks in Aerospace Science and Technology

The evolutionary structures of aerospace systems require a higher level of control strategies and the real-time assessment of possible risks for the successful implementation of designs and experiments in space conditions. This paper focuses on the Integrated Assessment and Control, Incorporated on the DMOCS architecture and the quantification of real-time uncertainty risk, in light of the International Space Station (ISS). The research investigates two primary objectives: first, the usefulness of DMOCS in establishing the optimal resource distribution to improve the functionality of distributed systems in spacecraft control, and second, the result of applying real-time uncertainty risk assessment techniques to increase the efficiency of space experimentations. A qualitative research approach was employed, and the data were gathered from scholarly journals, and official documents only. The thematic synthesis was conducted with a view of discovering different themes regarding optimization and risk assessment. Recommendations are made for the application of these strategies in long and high-risk space missions, and ideas are presented for future research in the areas of hybrid optimization and handling uncertainty.