Dual-system Co-evolution Method For Spacecraft Module Equipment Layout Design

The White Paper of 2016 China’s Spaceflight pointed out that how to improve the overall dynamic mass properties of spacecraft is of utmost importance in the design of the general layout scheme of multi-module spacecraft such as manned spaceflight,lunar exploration,space station,and Mars exploration,during the "Thirteenth Five-Year Plan" and a period of time in future.Mass property of spacecraft is one of the important data for spacecraft and launch vehicle coordination and also important basis for the performance design of the control system.They directly affect the performance,cost,installation and maintenance,the service life of the satellite system,as well as the success or failure of satellite missions.It is an important and difficult problem.The multi-modules spacecraft(or multi-bearing plate surfaces)equipment layout optimization problem(short for MSELOP hereinafter)in this dissertation belongs to the NP-Hard problem and engineering system layout optimization problem.It not only has computational complexity(combinatorial explosion),but also engineering complexity.As the design objectives and variables of MSELOP are increases,and higher computational accuracy is requires,it is better to adopt the strategy of divide and conquer and system decomposition to tackle this kind of engineering system optimization problem,for example,the cooperative co-evolutionary algorithm(CCEA).Therefore,how to allocate the spacecraft equipment and the overall layout optimization,under the premise of meeting the various technical requirements as far as possible to improve the overall dynamic mass properties of the spacecraft(the moment of inertia,the angle of inertia,the centroid and the product of inertia),for the current or future innovative research and development of spacecraft has important theoretical and engineering significance.The open problem is how to improve the computational performance(computational accuracy and robustness)of CCEA for the coupling engineering system optimization problems such as MSELOP.Therefore,this study takes the spacecraft(satellite)layout design projects as the engineering background,studies a new method of general layout optimization for MSELOP with the constraints of dynamic mass properties under the funding of National Natural Science Foundation of China.The general layout optimization includes equipment(components)distribution and the layout optimization of collaborative design.The proposed approach involves in processing cycle between component allocation and the layout optimization,interdependence coupling and coordination,makes every effort to solve a class of MSELOP.The purpose of this study is to improve the computational performance(computational accuracy and robustness)of CCEA,and the overall dynamic mass properties of the spacecraft module(the moment of inertia,the angle of inertia,the centroid and the product of inertia).The main work of this dissertation is shown as following:(1)How to improve the(computational accuracy and robustness)performance of CCEA for large scale(D=1000)nonseparable Benchmark function,this study presents a dual-system(A,B)cooperative coevolutionary algorithm(DCCDE,DCCDE/PSO).Firstly,an improved DE algorithm of DCCDE presents that is the local search strategy of simplex crossover(SPX),the mutation strategy pool and adaptive parameter combined with DE algorithm bring in the framework of dual system co-evolutionary evolutionary,which is conducted every several generations to improve exploration in the optimization process.Then,a migration pattern improves between the subsystems of dual-system(A,B),which increase the diversity of the population.The DCCDE/PSO studies from four aspects:the dual system structure,the system decomposition,the dual system coordination mechanism and the selection and matching of the hybrid algorithm in the CC framework.The experimental results of 25 nonseparable Benchmark functions show that the developed dual-system cooperative coevolutionary algorithm verifies the effectiveness and improves the computational performance(computational accuracy and robustness)of CCEA compared with single system CCEA.It is laid a solid foundation for the further study of MSELOP.(2)For MSELOP,this study presents a new dual-system(A,B)cooperative hybrid co-evolutionary algorithm NDCCDE/DPSO to further improve the computational performance(computational accuracy and robustness)of CCEA.Firstly,a new dual-system framework based on the Potter’s cooperative co-evolutionary(CC)is constructed and then,corresponding system decomposition rule,matrix analysis method and improved coordination mechanism are presented.Finally,the way of matching algorithms(e.g.evolutionary algorithms and swarm intelligence algorithms)with systems A and B in the dual system is presented.NDCCDE/DPSO is verified by two MSELOP.The experimental results show that the proposed NDCCDE/DPSO improves the computational performance(computational accuracy and robustness)of CCEA and improve the overall dynamic mass properties of the spacecraft module(the moment of inertia,the angle of inertia,the centroid and the product of inertia)compared with classical single-system CCEA algorithms and dual-system Potter’s cooperative co-evolutionary algorithms.(3)In the past,MSELOP rarely discussed the component allocation.It generally only discusses components layout based on the fixed component allocation scheme,which is presented in the initialization stage(including the initialized component allocation scheme),and doesn’t change during layout optimization.If the MSELOP adopts fixed component allocation scheme,which is unreasonable in the initialization stage,and mass and volume is unreasonable in the each module,which will seriously hinder the component layout optimization design,even can’t meet the design requirements of technical indicators(mass properties of spacecraft).Therefore,in order to solve the above problems and further improve the overall dynamic mass properties of the spacecraft,this study presents a dual-system co-evolutionary design method based on the multi agent system to solve the new problem of component allocation and layout optimization.The proposed dual-system cooperative co-evolutionary design method,through the cooperation and interaction among the agents and jointly solve the component distribution and layout optimization problems.The experimental results show that the presented dual-system co-evolutionary design method improves the computational accuracy and robustness,and verifies the effectiveness of the overall layout optimization method based on multi agents system compared with other components allocation method.The proposed method further improves the computational performance(computational accuracy and robustness)of CCEA and the overall dynamic mass properties of the spacecraft module(the moment of inertia,the angle of inertia,the centroid and the product of inertia).On the basis of the study stated above and previous work of research team,we present the system of spacecraft module equipment layout optimization and constructed the Pro/E 3-D model and achieve automatic virtual assembly design,based on Pro/Engineer software for reference and technical support to designer.The proposed dual-system cooperative co-evolutionary method tries to effectively solve the MSELOP,which has theoretical significance and application value.This study is hopes to apply and provide technical support to a class of coupled engineering system equipment allocation and layout such as special vehicle under-hood layout,engineering vehicle under-hood layout,and ship engine compartment layout.