A Study Of Constructing General Software Platform For Intelligent Payload Planning And Scheduling System

Along with the technical development of large spacecrafts and space platforms in our country, more and more advanced payloads will be put into use. Meanwhile, these payloads may need to work cooperatively to complete larger scale of experiment on space platforms, which makes payload's planning and scheduling problem more difficult. Planning and Scheduling run through the whole process from payload system design, analysis to application. Once the related parameter of any related procedure changed, the result of payload's planning and scheduling will be modified.It's hard to deal with this kind of complicated work only by handwork. Therefore, a set of universal and flexible software platform urgently need to be developed, which will be used to large spacecraft payload's planning and scheduling. This thesis refers to typical spacecraft planning and scheduling software such as ASPEN. Based on intelligent planning and scheduling theory, payload planning and scheduling is modeled as a Constraint Satisfaction Optimal Problem (CSOP), in which intelligent searching algorithms such as genetic algorithm and simulated annealing algorithm are used. Then basic elements for payload planning and scheduling are abstracted, which include time, activity, constraint, timeline and objective function. Subsequently, a software model is obtained. With supports of cell array and structure array in Matlab environment, data structure of elements mentioned above and user interface are designed. After user inputs parameters and elements through software interface, the software can autonomously complete payload's planning and scheduling.In this thesis, a kind of power-constraints problem can be dealt with by this software platform, and both intelligent algorithms are applied to a practical payload scheduling problem. Finally, conclusions are made and further researchs are explorered.