Spacecraft Design as a Multi-Criteria Decision-Making
The chapter deals with a method to automate the preliminary spacecraft design through a multi-criteria optimization process based on the fuzzy logic theory. The heart of the matter is to simulate the designers’ teams behavior in making refined choices within a universe of on-board subsystem solutions — to optimize, typically, the gross mass and the requested power of the whole space system. Decisions making is often based on qualitative relationships, driven by the selector’s expertise. The fuzzy logic theory revealed to be the best fitting method to model those kinds of mental processes. It permits to translate qualitative relationships, typically uncertain, into a precise mathematical formulation and it overcomes the Boolean representation true-false by defining a satisfaction degree of the inputs with respect to a set of given qualities.
Within the proposed method the optimal solution defines the propulsion, the communication, the power supply/power storage, the thermal control subsystem set and the launcher type. The solution minimizes the gross mass, the required power and the cost while it maximizes the reliability of the whole space system. The global index of merit, representing the output of the multi-criteria scalarization, identifies the feasible combinations of the selected alternative for the on-board systems. The goal vector scalarization is obtained through a preference function built with a configuration driven weight vector.
The core of the presented method is a variable weight vector that emphasizes the qualitative characteristics inherent a particular subsystem combination with respect to each selected goal function. A fuzzy control loop applies to each single subsystem alternative weight vector definition. Within each goal function, the weights related to every particular subsystem representing each possible final configuration is further elaborated through a particular matrix to obtain its four element weight vector. All quantities are treated as interval set and, then, managed with interval algebra rules.
Based on past space missions data, classic multi-criteria optimization methods (Pareto-surface detection) is considered. The proposed method provides the mission requirements (represented by objective function vectors and subsystems sets) definitely similar to those of real ones.
Keywordsanalytic hierarchical process fuzzy logic multi-criteria decision-making spacecraft design
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