LEADER 04646nam 22007215 450 001 9910746962803321 005 20230927173154.0 010 $a981-9943-11-6 024 7 $a10.1007/978-981-99-4311-1 035 $a(MiAaPQ)EBC30757740 035 $a(Au-PeEL)EBL30757740 035 $a(OCoLC)1401055585 035 $a(DE-He213)978-981-99-4311-1 035 $a(PPN)272736082 035 $a(CKB)28328635400041 035 $a(EXLCZ)9928328635400041 100 $a20230927d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvanced Trajectory Optimization, Guidance and Control Strategies for Aerospace Vehicles $eMethods and Applications /$fby Runqi Chai, Kaiyuan Chen, Lingguo Cui, Senchun Chai, Gokhan Inalhan, Antonios Tsourdos 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (272 pages) 225 1 $aSpringer Aerospace Technology,$x1869-1749 311 08$aPrint version: Chai, Runqi Advanced Trajectory Optimization, Guidance and Control Strategies for Aerospace Vehicles Singapore : Springer Singapore Pte. Limited,c2023 9789819943104 327 $aPart 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. 330 $aThis book focuses on the design and application of advanced trajectory optimization and guidance and control (G&C) techniques for aerospace vehicles. Part I of the book focuses on the introduction of constrained aerospace vehicle trajectory optimization problems, with particular emphasis on the design of high-fidelity trajectory optimization methods, heuristic optimization-based strategies, and fast convexification-based algorithms. In Part II, various optimization theory/artificial intelligence (AI)-based methods are constructed and presented, including dynamic programming-based methods, model predictive control-based methods, and deep neural network-based algorithms. Key aspects of the application of these approaches, such as their main advantages and inherent challenges, are detailed and discussed. Some practical implementation considerations are then summarized, together with a number of future research topics. The comprehensive and systematic treatment of practical issues in aerospace trajectory optimization and guidance and control problems is one of the main features of the book, which is particularly suitable for readers interested in learning practical solutions in aerospace trajectory optimization and guidance and control. The book is useful to researchers, engineers, and graduate students in the fields of G&C systems, engineering optimization, applied optimal control theory, etc. 410 0$aSpringer Aerospace Technology,$x1869-1749 606 $aControl engineering 606 $aAerospace engineering 606 $aAstronautics 606 $aComputational intelligence 606 $aMathematical optimization 606 $aControl and Systems Theory 606 $aAerospace Technology and Astronautics 606 $aComputational Intelligence 606 $aOptimization 615 0$aControl engineering. 615 0$aAerospace engineering. 615 0$aAstronautics. 615 0$aComputational intelligence. 615 0$aMathematical optimization. 615 14$aControl and Systems Theory. 615 24$aAerospace Technology and Astronautics. 615 24$aComputational Intelligence. 615 24$aOptimization. 676 $a629.12 700 $aChai$b Runqi$01225048 701 $aChen$b Kaiyuan$01431341 701 $aCui$b Lingguo$01431342 701 $aChai$b Senchun$01064463 701 $aInalhan$b Gokhan$01431343 701 $aTsourdos$b Antonios$0854294 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910746962803321 996 $aAdvanced Trajectory Optimization, Guidance and Control Strategies for Aerospace Vehicles$93573670 997 $aUNINA