Now showing items 1-10 of 28
A Measure of Worst-Case HPerformance and of Largest Acceptable Uncertainty
The structured singular value (SSV or ) is know to be an effective tool for assessing robust performance of linear time- invariant models subject to structured uncertainty. Yet all a single analysis provides is a bound ݠon ...
Nonmonotone Line Search for Minimax Problems
It was recently shown that, in the solution of smooth constrained optimization problems by sequential programming (SQP), the Maratos effect can be prevented by means of a certain nonmonotone (more precisely, four-step ...
Linear Fractional Transformations for the Approximation of Various Uncertainty Sets
Recently, it was shown that the structured singular value framework can be extended to the case when information on the phase of the uncertainty is available, and a computable upper bound on the corresponding "phase sensitive ...
A Simple quadratically convergent Interior Point Algorithm for Linear Programming and Convex quadratic Programming
An algorithm for linear programming (LP) and convex quadratic programming (CQP) is proposed, based on an interior point iteration introduced more than ten years ago by J. Herskovits for the solution of nonlinear programming ...
User's Guide for FSQP Version 2.0 A Fortran Code for Solving Optimization Problems, Possibly Minimax, with General Inequality Constraints and Linear Equality Constraints, Generating Feasible Iterates
FSQP 2.0 is a set of Fortran subroutines for the minimization of the maximum of a set of smooth objective functions (possibly a single one) subject to nonlinear smooth inequality constraints, linear inequality and linear ...
On Continuity/Discontinuity in Robustness Indicators
Continuity/discontinuity of robustness indicators is reviewed. For the case of real or mixed uncertainty, a regularization of the frequency dependent robustness margin is proposed and its properties are discussed. Implication ...
An SQP Algorithm for Finely Discretized Continuous Minimax Problems and Other Minimax Problems with Many Objective Functions
A common strategy for achieving global convergence in the solution of semi-infinite programming (SIP) problems, and in particular of continuous minimax problems, is to (approximately) solve a sequence of discretized problems, ...
User's Guide for ADIFFSQP Version 0.91
ADIFFSQP is a utility program that allows to user of the FFSQP constrained nonlinear optimization routines to invoke the computational differentiation (or automatic differentiation:AD) preprocessor ADIFOR2.0  conveniently
Absolute Stability Theory, Theory, and State-Space Verification of Frequency-Domain Conditions: Connections and Implications for Computation
The main contribution of the paper is to show the equivalence between the following two approaches for obtaining sufficient conditions for the robust stability of systems with structured uncertainties: (i) apply the classical ...
An SQP Algorithm for Finely Discretized SIP Problems and Other Problems with Many Constraints
A Common strategy for achieving global convergence in the solution of semi-infinite programming (SIP) problems is to (approximately) solve a sequence of discretized problems, with a progressively finer discretization mesh. ...