Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems

Runqi Chai

ISBN 10: 9811398445 / ISBN 13: 9789811398445

Published by Springer, Springer, 2019

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9789811398445

Bibliographic Details

• Title: Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems
• Publisher: Springer, Springer
• Publication Date: 2019
• Language: English
• ISBN 10: 9811398445
• ISBN 13: 9789811398445
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 18D millimeters 241 millimeters width by 160 millimeters height by 18 millimeters depth
• Weight: 512 grams

About this title

Synopsis

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.

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