Multidisciplinary Modeling and Collaborative Optimization of Mars Global Remote Sensing Probe

According to the analysis of the system parameters of Mars global remote sensing probe, the system optimization model considering remote sensing performance and total weight was established to achieve the distribution of the overall requirements based on the idea of decomposition and optimization of MDO(Multidisciplinary Design Optimization), which can be regarded as the input conditions of the sub-system. Based on the requirements and some parameters delivered from system optimization, many disciplines of the Mars probe such as the payload, the power supply and the control were analyzed including the variables and the constraints, thus the subsystem optimization models were obtained. The cooperative optimization method was used to decouple the parameters in both system and subsystem optimization models. Based on the adaptive dynamic penalty function method and the multiple optimization algorithms, which help to improve the convergence rate, the optimal parameters of the probe were obtained by solving the system and the subsystems optimization models. Therefore, the validity of applying the MDO method to the general design of the detector was verified.