Design of Trajectory Optimization Approach for Space Maneuver Vehicle Skip Entry Problems (Hardcover, 1st ed. 2020)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Springer Aerospace Technology
Release date:	August 2019
First published:	2020
Authors:	Runqi Chai • Al Savvaris • Antonios Tsourdos • Senchun Chai
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	207
Edition:	1st ed. 2020
ISBN-13:	978-981-13-9844-5
Categories:	Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Calculus of variations Books > Professional & Technical > Transport technology > Aerospace & aviation technology > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
LSN:	981-13-9844-5
Barcode:	9789811398445

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