The nonlinear dynamic response of atomic force microscopy cantilevers tapping on a sample is discussed through theoretical, computational, and experimental analysis. Experimental measurements are presented for the frequency response of a specific microcantilever-sample system to demonstrate the nonlinear features, including multiple jump phenomena leading to reproducible hysteresis. We show tha...

This paper presents a procedure for the identification of two types of a continuous-time linear system interconnected by direct and feedback memoryless nonlinearities. The first case is the continuous time Hammesrstein system and the second is a specific case of the continuous time Wiener system. The direct and feedback nonlinear elements, described by bounded unknown functions, are expressed a...

System identification often means the determination of linear models from input-output data. The behaviour of many systems can be described by an s-domain or z-domain transfer function model, at least for a given excitation amplitude range. The quality of the fit can be assessed by the analysis of the residuals, that is, of the difference between the measured data and the model. However, even s...

An approach to derive low-complexity models describing thermal radiation for the sake of simulating the behavior of electric arcs in switchgear systems is presented. The idea is to approximate the (high dimensional) full-order equations, modeling the propagation of the radiated intensity in space, with a model of much lower dimension, whose parameters are identified by means of nonlinear system...

This paper combines a conventional method of multivariablesystem identification with a dynamic multi-layer perceptron (MLP) toachieve a constructive method of nonlinear system identification. Theclassof nonlinear systems is assumed to operate nominally around anequilibrium point in the neighborhood of which a linearized model existsto represent the system, although norma...

Nonlinear structures exhibit complex behaviors that can be predicted and analyzed once a mathematical model of the structure is available. Obtaining such a model is a challenge. Several works in the literature suggest different methods for the identification of nonlinear structures. Some of the methods only address the question of whether the system is linear or not, other are more suitable for...

This paper addresses the experimental identification of a servo actuator which is used in many industrial applications. Because the system consisted of electrical and mechanical components, the behavior of the system was nonlinear. In addition, the under load behavior of this servo was different. The load torque was considered as the input and a two input-one output model was presented for t...

Design of controller for the process operation is typically based on the availability of the best model. Development of empirical model is incorporated with many assumptions and approximations. System identification is developed to alleviate this problem by considering the input and output data of the process for the model development. The cascaded tank process is highly nonlinear and non-minim...

Magneto-rheological damper is a nonlinear system. In this case study, system has been identified using Neural Network tool. Optimization between number of neurons in the hidden layer and number of epochs has been achieved and discussed by using multilayer perceptron Neural Network.

This paper is concerned with the parameter estimation of a general class of nonlinear dynamic systems in state-space form. More specifically, a Maximum Likelihood (ML) framework is employed and an Expectation Maximisation (EM) algorithm is derived to compute these ML estimates. The Expectation (E) step involves solving a nonlinear state estimation problem, where the smoothed estimates of the st...