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.

Optimal Trajectories in Atmospheric Flight deals with the optimization of trajectories in atmospheric flight. The book begins with a simple treatment of functional optimization followed by a discussion of switching theory. It then presents the derivation of the general equations of motion along with the basic knowledge in aerodynamics and propulsion necessary for the analysis of atmospheric flight trajectories. It goes on to the study of optimal trajectories by providing the general properties of the optimal aerodynamic controls and the integrals of motion. This is followed by discussions of high subsonic and supersonic flight, and approximation techniques to reduce the order of the problem for a fast computation of the optimal trajectory. The final chapters present analyses of optimal reentry trajectories and orbital maneuvers. This book is intended as a reference text for scientists and engineers wanting to get into the subject of optimal trajectories in atmospheric flight. If used for teaching purposes, the book is written in a self-contained way so that a selective use of the material is at the discretion of the lecturer. The first 11 chapters are sufficient for a one-semester course with emphasis on optimal maneuvers of high performance aircraft.

This is a long-overdue volume dedicated to space trajectory optimization. Interest in the subject has grown, as space missions of increasing levels of sophistication, complexity, and scientific return - hardly imaginable in the 1960s - have been designed and flown. Although the basic tools of optimization theory remain an accepted canon, there has been a revolution in the manner in which they are applied and in the development of numerical optimization. This volume purposely includes a variety of both analytical and numerical approaches to trajectory optimization. The choice of authors has been guided by the editor's intention to assemble the most expert and active researchers in the various specialities presented. The authors were given considerable freedom to choose their subjects, and although this may yield a somewhat eclectic volume, it also yields chapters written with palpable enthusiasm and relevance to contemporary problems.

This book presents a comprehensive overview of the recent advances in the domain of optimal guidance, exploring the characteristics of various optimal guidance algorithms and their pros and cons. Optimal guidance is based on the concept of trajectory optimization, which minimizes the meaningful performance index while satisfying certain terminal constraints, and by properly designing the cost function the guidance command can serve as a desired pattern for a variety of mission objectives. The book allows readers to gain a deeper understanding of how optimal guidance law can be utilized to achieve different mission objectives for missiles and UAVs, and also explores the physical meaning and working principle of different new optimal guidance laws. In practice, this information is important in ensuring confidence in the performance and reliability of the guidance law when implementing it in a real-world system, especially in aerospace engineering where reliability is the first priority.

Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 400 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments.

This book is devoted to the state-of-the-art in all aspects of fireworks algorithm (FWA), with particular emphasis on the efficient improved versions of FWA. It describes the most substantial theoretical analysis including basic principle and implementation of FWA and modeling and theoretical analysis of FWA. It covers exhaustively the key recent significant research into the improvements of FWA so far. In addition, the book describes a few advanced topics in the research of FWA, including multi-objective optimization (MOO), discrete FWA (DFWA) for combinatorial optimization, and GPU-based FWA for parallel implementation. In sequels, several successful applications of FWA on non-negative matrix factorization (NMF), text clustering, pattern recognition, and seismic inversion problem, and swarm robotics, are illustrated in details, which might shed new light on more real-world applications in future. Addressing a multidisciplinary topic, it will appeal to researchers and professionals in the areas of metahuristics, swarm intelligence, evolutionary computation, complex optimization solving, etc.