Wiener System Identification in Presence of Hysteresis Nonlinearity
نویسندگان
چکیده
The problem Wiener systems identification is addressed in presence of hysteresis nonlinearities, presently described by the Bouc-Wen model. The latter is nonlinear differential equation involving unknown parameters, some of which coming in nonlinearly. Except for stability, the linear subsystem is arbitrary and, in particular, it is not given a particular structure. By using sine excitations, the identification problem is reformulated as a set of nonlinear prediction-error optimization problems. The latter will be coped with using nonlinear least squares estimators which will formally be shown to be consistent.
منابع مشابه
Experimental Hysteresis Identification and Micro-position Control of a Shape-Memory-Alloy Rod Actuator
In order to exhaustively exploit the high-level capabilities of shape memory alloys (SMAs), they must be applied in control systems applications. However, because of their hysteretic inherent, dilatory response, and nonlinear behavior, scientists are thwarted in their attempt to design controllers for actuators of such kind. The current study aims at developing a micro-position control system ...
متن کاملHammerstein-Wiener Model: A New Approach to the Estimation of Formal Neural Information
A new approach is introduced to estimate the formal information of neurons. Formal Information, mainly discusses about the aspects of the response that is related to the stimulus. Estimation is based on introducing a mathematical nonlinear model with Hammerstein-Wiener system estimator. This method of system identification consists of three blocks to completely describe the nonlinearity of inp...
متن کاملSystem Identification in the Presence of a Saturation Nonlinearity
The paper deals with the identification of linear systems when they are in a pathway in series with a saturation nonlinearity. The objective is to estimate the parameters of the linear system and to obtain some characterisation of the nonlinearity, using only the input and output signals of the pathway. Both Wiener structures and Hammerstein structures are considered, and it is found that pertu...
متن کاملIdentification of a Wiener System via Semidefinite Programming
This paper presents a new method for the identification of Wiener systems in the presence of output noise. The Wiener system identification problem is formulated as a convex Semidefinite Programming (SDP) problem by constraining a finite dimensional time dependency between signals. The main contribution of this paper is that the proposed method is robust to output noise and neither the Gaussian...
متن کاملHysteresis Nonlinearity Identification Using New Preisach Model-Based Artificial Neural Network Approach
Preisach model is a well-known hysteresis identification method in which the hysteresis is modeled by linear combination of hysteresis operators. Although Preisach model describes the main features of system with hysteresis behavior, due to its rigorous numerical nature, it is not convenient to use in real-time control applications. Here a novel neural network approach based on the Preisach mod...
متن کامل