资源强耦合下改进遗传测控调度方法

With the development of spacecraft intelligence, an increase in the number of spacecraft and the complexity of missions lead to an increased demand for intelligent spacecraft measurement and control. The coupling degree of satellite TT&-C scheduling resources grows, and the Solution space dimension expands exponentially. However, existing methods limit the research on resource coupling issues, and the scheduling efficiency can not meet mission requirements. Aiming at the above problems, an improved genetic method for satellite TT&.C scheduling under strong resource coupling is proposed. Firstly, the multi-satellite TT&-C scheduling problem is modeled, and then the resource coupling in satellite TT&-C scheduling problem is analyzed, with the objective function and the hash table type dictionary of conflicting tasks defined. On the basis of genetic algorithm, a two-dimensional chromosome encoding form is designed that combines task sequences and benefits, and a multi-thread generation method is established for initializing the population with advantageous tasks. Multi-thread crossover and mutation operators for sequential decoupling are designed to efficiently process resource coupling Information in realtime according to gene order with the assistance of the conflicting-task dictionary. Finally, a scheduling Solution of task sequence is obtained through iteration. The results of three Simulation experiments demonstrate that this method has good convergence. Compared with the conventional genetic algorithm experiments, the average task benefit of this method increases by 21. 31%, and the average runtime decreases by 24. 36%. This validates the efficiency of the improved genetic method for satellite TT&-C scheduling under strong resource coupling, providing technical support for the Operation and management of intelligent spacecraft.