Subspace Identification of Periodically Switching Hammerstein-wiener Models for Magnetospheric Dynamics
نویسندگان
چکیده
Two existing Hammerstein-Wiener identification algorithms and a third novel Hammerstein-Wiener identification algorithm are considered for application to the magnetospheric system. A modified subspace algorithm that allows missing data points is described and used for identifying periodically switching Hammerstein-Wiener models, to capture the periodically time-varying nature of the system. These models are used to predict ground-based magnetometer response using the ACE satellite measurements.
منابع مشابه
Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms
Neural networks are applicable in identification systems from input-output data. In this report, we analyze theHammerstein-Wiener models and identify them. TheHammerstein-Wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsyst...
متن کاملDiscussion on: "Subspace-based Identification Algorithms for Hammerstein and Wiener Models"
1. Pearson RK. Selecting nonlinear model structures for computer control. J Process Control 2003; 13: 1–26 2. Bloemen HHJ, Chou CT, van den Boom TJJ, Verdult V, Verhaegen M, Backx TC. Wiener model identification and predictive control for dual composition control of a distillation column. J Process Control 2001; 11: 601–620 3. Westwick D, Verhaegen M. Identifying MIMO Wiener systems using subsp...
متن کاملIdentification of Aircraft Dynamics Using Hammerstein-Wiener Nonlinear Model
In this article, a new approach based on blockoriented nonlinear models for modeling and identification of aircraft nonlinear dynamics has been proposed. Some of the block-oriented nonlinear models are considered as flexible structures which are suitable for the identification of widely applicable dynamic systems. These models are able to approximate a wide range of system dynamics. Flying vehi...
متن کاملSubspace Identification of Multivariable Hammerstein and Wiener Models
In this paper, subspace-based algorithms for the simultaneous identification of the linear and nonlinear parts of multivariable Hammerstein and Wiener models are presented. The proposed algorithms consist basically of two steps. The first one is a standard (linear) subspace algorithm applied to an equivalent linear system whose inputs (respectively outputs) are filtered (by the nonlinear functi...
متن کاملCone Crusher Model Identification Using Block-Oriented Systems with Orthonormal Basis Functions
In this paper, block-oriented systems with linear parts based on Laguerre functions is used to approximation of a cone crusher dynamics. Adaptive recursive least squares algorithm is used to identification of Laguerre model. Various structures of Hammerstein, Wiener, Hammerstein-Wiener models are tested and the MATLAB simulation results are compared. The mean square error is used for models val...
متن کامل