predictive nonlinear model

In this paper, the finite horizon orbital optimization of a satellite launch vehicle based on nonlinear predictive model is presented. The proposed method optimizes the flight path variables such as the angle of attack parameters as well as the optimization of the trust value of each stage to achieve the maximum orbital altitude. In this method, the nominal path of the space carrier is obtained and compared with different optimization methods such as pattern search, sequential square programming and genetic algorithm. The resulting path is obtained based on the nominal conditions of the space carrier and by optimizing the variables of the angle of attack function. In this method, using the finite horizon optimization method, the optimal trust in each stage is accomplished with assuming that the total specific impact of each stage is constant. The flexibility of this method in solving optimization problems and the possibility of considering different flight path constraints are some of the advantages of this proposed limited horizon method. The proposed algorithm is used to optimize the orbital height of a native space carrier, and the simulation results show a 24 km increase in its orbital height relative to its nominal path conditions.