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Titlebook: Recent Advances in Optimization and its Applications in Engineering; Moritz Diehl,Francois Glineur,Wim Michiels Conference proceedings 201

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Using Model Order Reduction for the Parameter Optimization of Large Scale Dynamical Systemsl order reduction techniques to the parameter design problem of an acoustic cavity to accelerate the computation of both function values and derivatives, and therefore, drastically improve the performance of the optimization algorithms. Two types of model reduction techniques are explored: conventio
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Optimal Data Fitting on Lie Groups: a Coset Approachem of fitting affine subspaces in ℝ. to data which can be solved using principal component analysis. We show how the fitting problem can be reduced for biinvariant distances to a generalized mean calculation on an homogeneous space. For biinvariant Riemannian distances we provide an algorithm based
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Conference proceedings 2010nd engineering. The present book contains a careful selection of articles on recent advances in optimization theory, numerical methods, and their applications in engineering. It features in particular new methods and applications in the fields of optimal control, PDE-constrained optimization, nonlin
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y evolving body of fundamental theory, and a variety of exciting applications in science and engineering. The present book contains a careful selection of articles on recent advances in optimization theory, numerical methods, and their applications in engineering. It features in particular new metho
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On Hessian- and Jacobian-Free SQP Methods - a Total Quasi-Newton Scheme with Compact Storageounded by a bilinear order . instead of a cubic order . for standard SQP methods. Here .denotes the number of variables, . the maximal number of active constraints, and .the user-selected number of stored update vectors.
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Copositive Programming – a Surveyan understanding of the basic concepts and recent developments in copositive programming, including modeling issues and applications, the connection to semidefinite programming and sum-of-squares approaches, as well as algorithmic solution approaches for copositive programs.
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A Robust H∞ Quasi-LPV Approach for Designing Nonlinear Observersons are given in terms of linear matrix inequality constraints. These conditions ensure regional stability w.r.t. to a set of admissible initial conditions and also minimizes an upper-bound on the ..-gain of the error system. These results are applied to a high cell density bioreator.
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