Adaptive powered descent guidance based on multi-phase pseudospectral convex optimization

Abstract The real-time and fuel-optimal powered descent guidance is one of the critical technologies for planetary landing. This work focuses on the powered descent guidance algorithm based on pseudospectral convex optimization and aims to increase the accuracy and adaptability of the algorithm. The entire powered descent process is divided into phases according to the thrust switching times, and the pseudospectral method is adopted to discretize the optimization problem. Convexification process is performed to transform the optimization problem into a convex programming problem, and a successive solving process algorithm is proposed. For the established multi-phase pseudospectral convex optimization formulation, the indirect method is adopted to derive and determine the optimal phase division from switching function, and the adaptive multi-phase pseudospectral convex optimization method is proposed. Numerical examples demonstrate that the proposed method has excellent accuracy and adaptability.

[1]  Xinfu Liu,et al.  Fuel-optimal powered descent guidance with free final-time and path constraints , 2020 .

[2]  Ping Lu,et al.  The State of the Journal Is Strong , 2017 .

[3]  Yanning Guo,et al.  Fixed-time pinpoint mars landing using two sliding-surface autonomous guidance , 2019 .

[4]  Shuang Li,et al.  Overview of China’s 2020 Mars mission design and navigation , 2017, Astrodynamics.

[5]  Naigang Cui,et al.  Optimal Rocket Landing Guidance Using Convex Optimization and Model Predictive Control , 2019, Journal of Guidance, Control, and Dynamics.

[6]  George Leitmann,et al.  On a Class of Variational Problems in Rocket Flight , 1959 .

[7]  Marco Sagliano,et al.  Generalized hp Pseudospectral-Convex Programming for Powered Descent and Landing , 2018, Journal of Guidance, Control, and Dynamics.

[8]  F. Bennett.  Lunar descent and ascent trajectories , 1970 .

[9]  Stephen P. Boyd,et al.  ECOS: An SOCP solver for embedded systems , 2013, 2013 European Control Conference (ECC).

[10]  Michael Szmuk,et al.  Successive Convexification for Fuel-Optimal Powered Landing with Aerodynamic Drag and Non-Convex Constraints , 2016 .

[11]  Ping Lu,et al.  Introducing Computational Guidance and Control , 2017 .

[12]  M. A. Connor,et al.  Gravity turn trajectories through the atmosphere. , 1966 .

[13]  Allan R. Klumpp,et al.  Apollo lunar descent guidance , 1974, Autom..

[14]  F. V. Bennett.  Apollo lunar descent and ascent trajectories , 1970 .

[15]  Behçet Açikmese,et al.  Lossless Convexification of Nonconvex Control Bound and Pointing Constraints of the Soft Landing Optimal Control Problem , 2013, IEEE Transactions on Control Systems Technology.

[16]  Ping Lu,et al.  Survey of convex optimization for aerospace applications , 2017 .

[17]  Marco Sagliano,et al.  On the Radau pseudospectral method: theoretical and implementation advances , 2017, CEAS Space Journal.

[18]  Behcet Acikmese,et al.  Convex programming approach to powered descent guidance for mars landing , 2007 .

[19]  Behçet Açikmese,et al.  Successive convexification of non-convex optimal control problems and its convergence properties , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

[20]  James S. Meditch,et al.  On the problem of optimal thrust programming for a lunar soft landing , 1964 .

[21]  I. Michael Ross,et al.  Spectral Algorithm for Pseudospectral Methods in Optimal Control , 2008, Journal of Guidance, Control, and Dynamics.

[22]  Dangjun Zhao,et al.  Reentry trajectory optimization with waypoint and no-fly zone constraints using multiphase convex programming , 2017 .

[23]  Behcet Acikmese,et al.  Minimum-Landing-Error Powered-Descent Guidance for Mars Landing Using Convex Optimization , 2010 .

[24]  I. Michael Ross,et al.  Advances in Pseudospectral Methods for Optimal Control , 2008 .

[25]  Ping Lu,et al.  Celebrating Four Decades of Dedication and Excellence , 2018 .

[26]  Andrew E. Johnson,et al.  ADAPT demonstrations of onboard large-divert Guidance with a VTVL rocket , 2014, 2014 IEEE Aerospace Conference.

[27]  Marco Sagliano,et al.  Pseudospectral Convex Optimization for Powered Descent and Landing , 2017 .

[28]  P. Lu,et al.  Entry Trajectory Optimization by Second-Order Cone Programming , 2016 .

[29]  Erwin Mooij,et al.  Optimal Drag-Energy Entry Guidance via Pseudospectral Convex Optimization , 2018 .

[30]  Bin Li,et al.  Spacecraft close-range trajectory planning via convex optimization and multi-resolution technique , 2020 .

[31]  Pedro Simplício,et al.  Guidance of Reusable Launchers: Improving Descent and Landing Performance , 2019, Journal of Guidance, Control, and Dynamics.

[32]  Hongwei Yang,et al.  Rapid Generation of Time-Optimal Trajectories for Asteroid Landing via Convex Optimization , 2017 .

[33]  Ping Lu,et al.  Theory of Fractional-Polynomial Powered Descent Guidance. , 2020, Journal of guidance, control, and dynamics : a publication of the American Institute of Aeronautics and Astronautics devoted to the technology of dynamics and control.

[34]  Richard W. Powell,et al.  Systems for pinpoint landing at Mars , 2004 .

[35]  Xiaoming X. Cheng,et al.  Efficient ascent trajectory optimization using convex models based on the Newton–Kantorovich/Pseudospectral approach , 2017 .

[36]  Ronald R. Sostaric,et al.  Powered Descent Guidance Methods For The Moon and Mars , 2005 .

[37]  Yang Cheng,et al.  Toward improved landing precision on Mars , 2011, 2011 Aerospace Conference.

[38]  Ping Lu,et al.  Augmented Apollo Powered Descent Guidance , 2019, Journal of Guidance, Control, and Dynamics.

[39]  I. Michael Ross,et al.  Direct Trajectory Optimization by a Chebyshev Pseudospectral Method ; Journal of Guidance, Control, and Dynamics, v. 25, 2002 ; pp. 160-166 , 2002 .