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.