Thr formulation and analysis of numerical methods for inverse Eigenvalue problems
SIAM Journal on Numerical Analysis
Numerical methods for inverse singular value problems3
SIAM Journal on Numerical Analysis
SIAM Review
Complementarity and nondegeneracy in semidefinite programming
Mathematical Programming: Series A and B
Alternating projection algorithms for linear matrix inequalities problems with rank constraints
Advances in linear matrix inequality methods in control
Bilinearity and complementarity in robust control
Advances in linear matrix inequality methods in control
Optimization by Vector Space Methods
Optimization by Vector Space Methods
Robust Control via Sequential Semidefinite Programming
SIAM Journal on Control and Optimization
A Newton-like method for solving rank constrained linear matrix inequalities
Automatica (Journal of IFAC)
Paper: Low-order control design for LMI problems using alternating projection methods
Automatica (Journal of IFAC)
Decentralized robust control of uncertain Markov jump parameter systems via output feedback
Automatica (Journal of IFAC)
Brief paper: Multivariable PID control with set-point weighting via BMI optimisation
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Brief paper: Decentralised static output feedback stabilisation and synchronisation of networks
Automatica (Journal of IFAC)
Local mode dependent output feedback control of uncertain Markovian jump large-scale systems
ACC'09 Proceedings of the 2009 conference on American Control Conference
A Newton-like method for solving rank constrained linear matrix inequalities
Automatica (Journal of IFAC)
Generalized pole placement via static output feedback: A methodology based on projections
Automatica (Journal of IFAC)
Lyapunov functions for time-relevant 2D systems, with application to first-orthant stable systems
Automatica (Journal of IFAC)
Distributed robust estimation over randomly switching networks using H ∞ consensus
Automatica (Journal of IFAC)
Hi-index | 22.16 |
This paper presents a Newton-like algorithm for solving systems of rank constrained linear matrix inequalities. Though local quadratic convergence of the algorithm is not a priori guaranteed or observed in all cases, numerical experiments, including application to an output feedback stabilization problem, show the effectiveness of the algorithm.