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This book explores the design of optimal trajectories for space maneuver vehicles (SMVs) using optimal control-based techniques. It begins with a comprehensive introduction to and overview of three main approaches to trajectory optimization, and subsequently focuses on the design of a novel hybrid optimization strategy that combines an initial guess generator with an improved gradient-based inner optimizer. Further, it highlights the development of multi-objective spacecraft trajectory optimization problems, with a particular focus on multi-objective transcription methods and multi-objective evolutionary algorithms. In its final sections, the book studies spacecraft flight scenarios with noise-perturbed dynamics and probabilistic constraints, and designs and validates new chance-constrained optimal control frameworks.
The comprehensive and systematic treatment of practical issues in spacecraft trajectory optimization is one of the book's major features, making it particularly suited for readers who are seeking practical solutions in spacecraft trajectory optimization. It offers a valuable asset for researchers, engineers, and graduate students in GNC systems, engineering optimization, applied optimal control theory, etc.
List of contents
Introduction.- Overview of Trajectory Optimization Techniques.- Modelling of the Trajectory Optimization Problems.- Performance Analysis of Different Optimization Strategies.- Hybrid Optimization Methods with Enhanced Convergence Ability.- Multi-Objective Trajectory Optimization Problem.- Real-Time Optimal Guidance Strategies for Space Maneuver Vehicles.- Stochastic Trajectory Optimization Problems with Chance Constraints.- Appendix.- References.- Index.
About the author
Dr. Runqi Chai’s research interests include spacecraft trajectory optimization, multi-objective optimization, optimal control theory, model predictive control and chance-constrained optimization. Currently he serves as an active reviewer for several international publications including IEEE and AIAA.
The list of Runqi Chai’s publications is as follows:
R. Chai, A. Savvaris, A. Tsourdos, S. Chai, and Y. Xia, Trajectory Optimization of Space Maneuver Vehicle Using a Hybrid Optimal Control Solver. IEEE Transactions on Cybernetics, 2019, vol. 49, no. 2, pp. 467-480
R. Chai, A. Savvaris, and S. Chai*, Integrated missile guidance and control using optimization-based predictive control, Nonlinear Dynamics, 2019, 1-17, Available online.
R. Chai, A. Savvaris, A. Tsourdos, S. Chai*, and Y. Xia, Optimal fuel consumption finite-thrust orbital hopping of aeroassisted spacecraft, Aerospace Science and Technology, 2018, vol. 75, no. 4, pp. 172-182
Summary
This book explores the design of optimal trajectories for space maneuver vehicles (SMVs) using optimal control-based techniques. It begins with a comprehensive introduction to and overview of three main approaches to trajectory optimization, and subsequently focuses on the design of a novel hybrid optimization strategy that combines an initial guess generator with an improved gradient-based inner optimizer. Further, it highlights the development of multi-objective spacecraft trajectory optimization problems, with a particular focus on multi-objective transcription methods and multi-objective evolutionary algorithms. In its final sections, the book studies spacecraft flight scenarios with noise-perturbed dynamics and probabilistic constraints, and designs and validates new chance-constrained optimal control frameworks.
The comprehensive and systematic treatment of practical issues in spacecraft trajectory optimization is one of the book’s major features, making it particularly suited for readers who are seeking practical solutions in spacecraft trajectory optimization. It offers a valuable asset for researchers, engineers, and graduate students in GNC systems, engineering optimization, applied optimal control theory, etc.
