First and second order analysis of nonlinear semidefinite programs
Mathematical Programming: Series A and B
Robust Control via Sequential Semidefinite Programming
SIAM Journal on Control and Optimization
Primal-Dual Interior-Point Methods for Self-Scaled Cones
SIAM Journal on Optimization
SIAM Journal on Optimization
SIAM Journal on Optimization
Primal--Dual Path-Following Algorithms for Semidefinite Programming
SIAM Journal on Optimization
On the Nesterov--Todd Direction in Semidefinite Programming
SIAM Journal on Optimization
SIAM Journal on Optimization
A Global Algorithm for Nonlinear Semidefinite Programming
SIAM Journal on Optimization
Successive Linearization Methods for Nonlinear Semidefinite Programs
Computational Optimization and Applications
Spectral bundle methods for non-convex maximum eigenvalue functions: second-order methods
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
The rate of convergence of the augmented Lagrangian method for nonlinear semidefinite programming
Mathematical Programming: Series A and B
Local convergence of an augmented Lagrangian method for matrix inequality constrained programming
Optimization Methods & Software
Mathematical Programming: Series A and B
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In this paper, for solving the nonlinear semidefinite programming problem, a homotopy is constructed by using the parameterized matrix inequality constraint. Existence of a smooth path determined by the homotopy equation, which starts from almost everywhere and converges to a Karush---Kuhn---Tucker point, is proven under mild conditions. A predictor-corrector algorithm is given for numerically tracing the smooth path. Numerical tests with nonlinear semidefinite programming formulations of several control design problems with the data contained in COMPl e ib are done. Numerical results show that the proposed algorithm is feasible and applicable.