AuthorCannarsa, Piermarco. author
TitleSemiconcave Functions, HamiltonโJacobi Equations, and Optimal Control [electronic resource] / by Piermarco Cannarsa, Carlo Sinestrari
ImprintBoston, MA : Birkhรคuser Boston, 2004
Connect tohttp://dx.doi.org/10.1007/b138356
Descript XIV, 304 p. online resource

SUMMARY

Semiconcavity is a natural generalization of concavity that retains most of the good properties known in convex analysis, but arises in a wider range of applications. This text is the first comprehensive exposition of the theory of semiconcave functions, and of the role they play in optimal control and Hamilton-Jacobi equations. The first part covers the general theory, encompassing all key results and illustrating them with significant examples. The latter part is devoted to applications concerning the Bolza problem in the calculus of variations and optimal exit time problems for nonlinear control systems. The exposition is essentially self-contained since the book includes all prerequisites from convex analysis, nonsmooth analysis, and viscosity solutions. A central role in the present work is reserved for the study of singularities. Singularities are first investigated for general semiconcave functions, then sharply estimated for solutions of Hamilton-Jacobi equations, and finally analyzed in connection with optimal trajectories of control systems. Researchers in optimal control, the calculus of variations, and partial differential equations will find this book useful as a state-of-the-art reference for semiconcave functions. Graduate students will profit from this text as it provides a handyโyet rigorousโintroduction to modern dynamic programming for nonlinear control systems


CONTENT

A Model Problem -- Semiconcave Functions -- Generalized Gradients and Semiconcavity -- Singularities of Semiconcave Functions -- Hamilton-Jacobi Equations -- Calculus of Variations -- Optimal Control Problems -- Control Problems with Exit Time


SUBJECT

  1. Mathematics
  2. Measure theory
  3. Partial differential equations
  4. Mathematical optimization
  5. Mathematics
  6. Partial Differential Equations
  7. Measure and Integration
  8. Optimization