Abstract
The real-time guidance algorithm is the key technology of the powered landing. Given the lack of real-time performance of the convex optimization algorithm with free final time, a lossless convex optimization (LCvx) algorithm based on the deep neural network (DNN) predictor is proposed. Firstly, the DNN predictor is built to map the optimal final time. Then, the LCvx algorithm is used to solve the problem of fuel-optimal powered landing with the given final time. The optimality and real-time performance of the proposed algorithm are verified by numerical examples. Finally, a closed-loop simulation framework is constructed, and the accuracy of landing under various disturbances is verified. The proposed method does not need complex iterative operations compared with the traditional algorithm with free final time. Therefore, the computational efficiency can be improved by an order of magnitude.
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