Closed-Loop Subspace Identification for Stable/ Unstable Systems Using Data Compression and Nuclear Norm Minimization
نویسندگان
چکیده
This paper provides a subspace method for closed-loop identification, which clearly specifies the model order from noisy measurement data. The can handle long I/O data of target system to be noise-tolerant and determine via nuclear norm minimization. First, proposed compresses by projecting them an appropriate low dimensional subspace, then obtains whose is specified combination compression Its effectiveness demonstrated through detailed numerical examples.
منابع مشابه
Subspace Identification using Closed-Loop Data
The purpose of this thesis was to investigate how different subspace identification methods cope with closed loop data, and how the controller parameters affect the quality of the acquired models. Three different subspace methods were subject for investigation; the MOESPmethod, theN4SIDmethod and theDSR_emethod. It is shown through a simulation example that all three subspace methods will ident...
متن کاملSubspace identification from closed loop data
So called subspace methods for direct identiication of linear models in state space form have drawn considerable interest recently. They have been found to work well in many cases but have one drawback { they do not yield consistent estimates for data collected under output feedback. This contribution points to the reasons for this and also shows how to modify the basic algorithm to handle clos...
متن کاملNuclear Norm Minimization via Active Subspace Selection
We describe a novel approach to optimizing matrix problems involving nuclear norm regularization and apply it to the matrix completion problem. We combine methods from non-smooth and smooth optimization. At each step we use the proximal gradient to select an active subspace. We then find a smooth, convex relaxation of the smaller subspace problems and solve these using second order methods. We ...
متن کاملHammerstein system identification using nuclear norm minimization
This paper presents a new method for the identification of Hammerstein systems. The parameter estimation problem is formulated as a rank minimization problem by constraining a finite dimensional time dependency between signals. Due to the unknown intermediate signal, the rank minimization problem cannot be solved directly. Thus, the rank minimization problem is reformulated as an intermediate s...
متن کاملN2SID: Nuclear Norm Subspace Identification
The identification of multivariable state space models in innovation form is solved in a subspace identification framework using convex nuclear norm optimization. The convex optimization approach allows to include constraints on the unknown matrices in the data-equation characterizing subspace identification methods, such as the lower triangular block-Toeplitz of weighting matrices constructed ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2022
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2022.3154017