04640nam 22007215 450 991074696280332120251116200231.0981-9943-11-610.1007/978-981-99-4311-1(MiAaPQ)EBC30757740(Au-PeEL)EBL30757740(OCoLC)1401055585(DE-He213)978-981-99-4311-1(PPN)272736082(CKB)28328635400041(EXLCZ)992832863540004120230927d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAdvanced Trajectory Optimization, Guidance and Control Strategies for Aerospace Vehicles Methods and Applications /by Runqi Chai, Kaiyuan Chen, Lingguo Cui, Senchun Chai, Gokhan Inalhan, Antonios Tsourdos1st ed. 2023.Singapore :Springer Nature Singapore :Imprint: Springer,2023.1 online resource (272 pages)Springer Aerospace Technology,1869-1749Print version: Chai, Runqi Advanced Trajectory Optimization, Guidance and Control Strategies for Aerospace Vehicles Singapore : Springer Singapore Pte. Limited,c2023 9789819943104 Part I Advanced trajectory optimization methods -- Chapter 1 Review of advanced trajectory optimization methods -- Chapter 2 Heurestic optimization-based trajectory optimization -- Chapter 3 Highly fidelity trajectory optimization -- Chapter 4 Fast trajectory optimization with chance constraints -- Chapter 5 Fast generation of chance-constrained flight trajectory for unmanned vehicles -- Part II Advanced guidance and control methods for aerospace vehicles -- Chapter 6 Review of advanced guidance and control methods -- Chapter 7 Optimization-based predictive G&C method -- Chapter 8 Robust model predictive control for attitude control tracking.This book focuses on the design and application of advanced trajectory optimization and guidance and control (G&C) techniques for aerospace vehicles. Part I of the book focuses on the introduction of constrained aerospace vehicle trajectory optimization problems, with particular emphasis on the design of high-fidelity trajectory optimization methods, heuristic optimization-based strategies, and fast convexification-based algorithms. In Part II, various optimization theory/artificial intelligence (AI)-based methods are constructed and presented, including dynamic programming-based methods, model predictive control-based methods, and deep neural network-based algorithms. Key aspects of the application of these approaches, such as their main advantages and inherent challenges, are detailed and discussed. Some practical implementation considerations are then summarized, together with a number of future research topics. The comprehensive and systematic treatment of practical issues in aerospace trajectory optimization and guidance and control problems is one of the main features of the book, which is particularly suitable for readers interested in learning practical solutions in aerospace trajectory optimization and guidance and control. The book is useful to researchers, engineers, and graduate students in the fields of G&C systems, engineering optimization, applied optimal control theory, etc.Springer Aerospace Technology,1869-1749Automatic controlAerospace engineeringAstronauticsComputational intelligenceMathematical optimizationControl and Systems TheoryAerospace Technology and AstronauticsComputational IntelligenceOptimizationAutomatic control.Aerospace engineering.Astronautics.Computational intelligence.Mathematical optimization.Control and Systems Theory.Aerospace Technology and Astronautics.Computational Intelligence.Optimization.629.12Chai Runqi1225048Chen Kaiyuan1431341Cui Lingguo1431342Chai Senchun1064463İnalhan Gökhan0Tsourdos Antonios854294MiAaPQMiAaPQMiAaPQBOOK9910746962803321Advanced Trajectory Optimization, Guidance and Control Strategies for Aerospace Vehicles3573670UNINA