Six-DOF Spacecraft Optimal Trajectory Planning and Real-Time Attitude Control: A Deep Neural Network-Based Approach
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- 23 December 2019
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Neural Networks and Learning Systems
- Vol. 31 (11) , 5005-5013
Abstract
This brief presents an integrated trajectory planning and attitude control framework for six-degree-of-freedom (6-DOF) hypersonic vehicle (HV) reentry flight. The proposed framework utilizes a bilevel structure incorporating desensitized trajectory optimization and deep neural network (DNN)-based control. In the upper level, a trajectory data set containing optimal system control and state trajectories is generated, while in the lower level control system, DNNs are constructed and trained using the pregenerated trajectory ensemble in order to represent the functional relationship between the optimized system states and controls. These well-trained networks are then used to produce optimal feedback actions online. A detailed simulation analysis was performed to validate the real-time applicability and the optimality of the designed bilevel framework. Moreover, a comparative analysis was also carried out between the proposed DNN-driven controller and other optimization-based techniques existing in related works. Our results verify the reliability of using the proposed bilevel design for the control of HV reentry flight in real time.Keywords
This publication has 33 references indexed in Scilit:
- Robust model predictive tracking control of hypersonic vehicles in the presence of actuator constraints and input delaysJournal of the Franklin Institute, 2016
- Application of Taylor-Series Integration to Reentry Problems with WindJournal of Guidance, Control, and Dynamics, 2016
- Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic ProgrammingIEEE Transactions on Neural Networks and Learning Systems, 2016
- Pigeon-inspired optimization applied to constrained gliding trajectoriesNonlinear Dynamics, 2015
- Finite-Time Attitude Tracking of Spacecraft With Fault-Tolerant CapabilityIEEE Transactions on Control Systems Technology, 2014
- Real-Time Trajectory and Attitude Coordination Control for Reusable Launch Vehicle in Reentry PhaseIEEE Transactions on Industrial Electronics, 2014
- Particle Swarm Optimization Applied to Spacecraft Reentry TrajectoryJournal of Guidance, Control, and Dynamics, 2013
- Neural Network-Based Distributed Attitude Coordination Control for Spacecraft Formation Flying With Input SaturationIEEE Transactions on Neural Networks and Learning Systems, 2012
- A Survey of Methods Available for the Numerical Optimization of Continuous Dynamic SystemsJournal of Optimization Theory and Applications, 2011
- Integrated Adaptive Guidance and Control for Re-Entry Vehicles with Flight Test ResultsJournal of Guidance, Control, and Dynamics, 2004