Abstract This paper presents the computation of the non‐parametric uncertainty model for multi input multi output (MIMO) systems, which is described by normalized coprime factors (NCF) using the frequency response data of the system. This computation is accomplished by minimizing a υ‐gap metric criterion. For this purpose, the problem is formulated to a convex optimization context, such that a semidefinite programming (SDP) can be implemented. Minimization constraints and the normality constraints of coprime factors are converted to linear matrix inequalities (LMI). Thus, by convex optimization algorithms, the semidefinite programming will be optimized. The proposed method can also be used for non‐square multi input multi output systems in ...
This paper discusses the design of a multiantenna transmitter in a multi-input, multi-output channel...
Frequency response data collection can be a boon for modeling of MIMO uncertain plant. System stabil...
Abstract—Maximum (or `∞) norm minimization subject to an underdetermined system of linear equations ...
Modeling of uncertain systems with normalized coprime factor description is investigated where the e...
Modeling of uncertain systems with normalized coprime factor description is investigated where the e...
[[abstract]]This research develops a reliable and systematic low-order controller design method for ...
Closed-loop identification of the multi-input multi-output (MIMO) process is studied. Models of copr...
Abstract—Many different excitation signals can be chosen for the nonparametric frequency response fu...
This paper studies the problem of H-2 norm checking for a MIMO system with parameter uncertainties. ...
Minimization of the `1 (or maximum) norm subject to a constraint that imposes consistency to an unde...
Minimization of the ` ∞ (or maximum) norm subject to a constraint that imposes consistency to an und...
The problem of checking robust D-stability of multi-in and multi-out (MIMO) systems was studied. Thr...
Computation of all possible frequency responses of a linear system that depends on M uncertain param...
This paper addresses the problem of model reduction for uncertain discrete-time systems with convex ...
This work presents a framework to address the problem of designing discrete-time LTI (linear and tim...
This paper discusses the design of a multiantenna transmitter in a multi-input, multi-output channel...
Frequency response data collection can be a boon for modeling of MIMO uncertain plant. System stabil...
Abstract—Maximum (or `∞) norm minimization subject to an underdetermined system of linear equations ...
Modeling of uncertain systems with normalized coprime factor description is investigated where the e...
Modeling of uncertain systems with normalized coprime factor description is investigated where the e...
[[abstract]]This research develops a reliable and systematic low-order controller design method for ...
Closed-loop identification of the multi-input multi-output (MIMO) process is studied. Models of copr...
Abstract—Many different excitation signals can be chosen for the nonparametric frequency response fu...
This paper studies the problem of H-2 norm checking for a MIMO system with parameter uncertainties. ...
Minimization of the `1 (or maximum) norm subject to a constraint that imposes consistency to an unde...
Minimization of the ` ∞ (or maximum) norm subject to a constraint that imposes consistency to an und...
The problem of checking robust D-stability of multi-in and multi-out (MIMO) systems was studied. Thr...
Computation of all possible frequency responses of a linear system that depends on M uncertain param...
This paper addresses the problem of model reduction for uncertain discrete-time systems with convex ...
This work presents a framework to address the problem of designing discrete-time LTI (linear and tim...
This paper discusses the design of a multiantenna transmitter in a multi-input, multi-output channel...
Frequency response data collection can be a boon for modeling of MIMO uncertain plant. System stabil...
Abstract—Maximum (or `∞) norm minimization subject to an underdetermined system of linear equations ...