By Christian Kirches
Christian Kirches develops a quick numerical set of rules of huge applicability that successfully solves mixed-integer nonlinear optimum keep an eye on difficulties. He makes use of convexification and rest thoughts to acquire computationally tractable reformulations for which feasibility and optimality certificate might be given even after discretization and rounding.
Read Online or Download Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control PDF
Similar nonfiction_5 books
Social constructionism (2nd edition)
This available, but scholarly, textbook goals to introduce scholars to the world of social technological know-how conception and examine that has grow to be referred to as social constructionism. utilizing numerous examples from daily adventure and from present examine in parts similar to character, sexuality and well-being, the fundamental theoretical assumptions of social constructionism are basically defined.
Poisonous hearth effluents are answerable for nearly all of hearth deaths, and an expanding huge majority of fireside accidents, pushed by way of the common and extending use of man-made polymers. hearth protection has excited by fighting ignition and lowering flame unfold via decreasing the speed of warmth unlock, whereas neglecting the $64000 factor of fireside toxicity.
- Paint & Coating Industry December 2011
- Was (Fantasy Masterworks 43)
- True and False Recovered Memories: Toward a Reconciliation of the Debate
- Molecular Biomineralization: Aquatic Organisms Forming Extraordinary Materials
- [Magazine] Scientific American Mind. Vol. 16. No 3
Extra info for Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control
Example text
Chapter 9 presents numerical results for all new algorithms and makes comparisons to existing methods at the example of several mixed–integer optimal control and mixed–integer NMPC problems. In an extensive industrial case study, a challenging mixed–integer nonlinear model predictive control problem is solved under demanding real–time constraints. We show that by using the developed numerical methods, this problem could even be solved on an embedded system with limited computational resources. This thesis is closed by appendix A, containing details on the implementation of the developed algorithms within the software packages MuShROOM and qpHPSC.
2 Solution Methods for Optimal Control Problems 19 The disadvantages of indirect methods are quite obvious, however. The necessary conditions of optimality have to be derived analytically for every problem instance, and require several different special cases to be distinguished. In particular, general path and control constraints c(·) frequently lead to an a priori unknown structure of the optimal solution. g. the introduction of an additional constraint, as the optimal solution’s structure often is very sensitive to changes of the problem data.
Finally, the direct multiple shooting method is presented as a hybrid approach combining the advantages of both direct methods. We go into more detail here, as all numerical algorithms presented in this thesis are based on and focused on direct multiple shooting. 1 Indirect Methods Indirect methods are based on Pontryagin’s Maximum Principle and optimize in an infinite–dimensional function space. Necessary conditions of optimality are used to transform the optimal control problem into a Multi–Point Boundary Value Problem (MPBVP), which can then be solved by appropriate numerical methods.