00456nam 2200157z- 450 9910712605103321(CKB)5470000002496116(EXLCZ)99547000000249611620230509c2007uuuu -u- -engIntroduction to shaped chargesAberdeen Proving Ground, MDArmy Research LaboratoryBOOK9910712605103321Introduction to shaped charges3263196UNINA04388nam 22005655 450 991048383950332120200706120443.03-030-41846-410.1007/978-3-030-41846-5(CKB)4100000011243554(MiAaPQ)EBC6199424(DE-He213)978-3-030-41846-5(PPN)248395084(EXLCZ)99410000001124355420200513d2020 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierRelative Optimization of Continuous-Time and Continuous-State Stochastic Systems /by Xi-Ren Cao1st ed. 2020.Cham :Springer International Publishing :Imprint: Springer,2020.1 online resource (376 pages)Communications and Control Engineering,0178-53543-030-41845-6 Chapter 1. Introduction -- Chapter 2. Optimal Control of Markov Processes: Infinite Horizon -- Chapter 3. Optimal Control of Diffusion Processes -- Chapter 4. Degenerate Diffusion Processes -- Chapter 5. Multi-Dimensional Diffusion Processes -- Chapter 6. Performance-Derivative-Based Optimization -- Appendices -- Index.This monograph applies the relative optimization approach to time nonhomogeneous continuous-time and continuous-state dynamic systems. The approach is intuitively clear and does not require deep knowledge of the mathematics of partial differential equations. The topics covered have the following distinguishing features: long-run average with no under-selectivity, non-smooth value functions with no viscosity solutions, diffusion processes with degenerate points, multi-class optimization with state classification, and optimization with no dynamic programming. The book begins with an introduction to relative optimization, including a comparison with the traditional approach of dynamic programming. The text then studies the Markov process, focusing on infinite-horizon optimization problems, and moves on to discuss optimal control of diffusion processes with semi-smooth value functions and degenerate points, and optimization of multi-dimensional diffusion processes. The book concludes with a brief overview of performance derivative-based optimization. Among the more important novel considerations presented are: the extension of the Hamilton–Jacobi–Bellman optimality condition from smooth to semi-smooth value functions by derivation of explicit optimality conditions at semi-smooth points and application of this result to degenerate and reflected processes; proof of semi-smoothness of the value function at degenerate points; attention to the under-selectivity issue for the long-run average and bias optimality; discussion of state classification for time nonhomogeneous continuous processes and multi-class optimization; and development of the multi-dimensional Tanaka formula for semi-smooth functions and application of this formula to stochastic control of multi-dimensional systems with degenerate points. The book will be of interest to researchers and students in the field of stochastic control and performance optimization alike.Communications and Control Engineering,0178-5354Automatic controlCalculus of variationsMarkov processesControl and Systems Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/T19010Calculus of Variations and Optimal Control; Optimizationhttps://scigraph.springernature.com/ontologies/product-market-codes/M26016Markov modelhttps://scigraph.springernature.com/ontologies/product-market-codes/M27010Automatic control.Calculus of variations.Markov processes.Control and Systems Theory.Calculus of Variations and Optimal Control; Optimization.Markov model.519.703Cao Xi-Renauthttp://id.loc.gov/vocabulary/relators/aut771929MiAaPQMiAaPQMiAaPQBOOK9910483839503321Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems2843743UNINA