Identification of Nonlinear Nonautonomous State Space Systems from Input-Output Measurements
نویسندگان
چکیده
Ab~tract-This paper presents a method to determine a nonlinear state space model from a 6nite number of measurements of the inputs and outputs. The method is based on embedding theory for nonlinear systems, and can be viewed as an extension of the subspace identification method for linear systems. The paper describes the underlying theory and provides some guidelines for using the method in practice. To illustrate the use of the idenfillcation method, it was applied to a second-order nonlinear system.
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 کاملOnline State Space Model Parameter Estimation in Synchronous Machines
The purpose of this paper is to present a new approach based on the Least Squares Error method for estimating the unknown parameters of the nonlinear 3rd order synchronous generator model. The proposed method uses the mathematical relationships between the machine parameters and on-line input/output measurements to estimate the parameters of the nonlinear state space model. The field voltage is...
متن کاملNonlinear Identification of Hydraulic Servo-Drive Systems
his article deals with the identification of nonlinear models T in observer canonical form of hydraulic servo-drives from sampled data of input-output measurements. The data are processed by a modified Recursive Instrumental Variables algorithm, to provide input-output relationships of the plant dynamics. From the parameters of the input-output relations, continuous state-space nonlinear models...
متن کاملAdaptive fuzzy pole placement for stabilization of non-linear systems
A new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. We use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. Then, we linearized this identified model at each sampling time to have an approximate linear time varying system. In order to stabilize...
متن کاملAdaptive Input-Output Linearization Control of pH Processes
pH control is a challenging problem due to its highly nonlinear nature. In this paper the performances of two different adaptive global linearizing controllers (GLC) are compared. Least squares technique has been used for identifying the titration curve. The first controller is a standard GLC based on material balances of each species. For implementation of this controller a nonlinear state...
متن کامل