A Sequential Algebraic Parametric Identification Approach for Nonlinear Vibrating Mechanical Systems

2017 ◽  
Vol 19 (4) ◽  
pp. 1564-1574 ◽  
Author(s):  
F. Beltran-Carbajal ◽  
G. Silva-Navarro ◽  
L. G. Trujillo-Franco
Keyword(s):  
Mechanical Systems ◽  
Parametric Identification ◽  
Identification Approach

scholarly journals Algebraic Parameter Identification of Nonlinear Vibrating Systems and Non Linearity Quantification Using the Hilbert Transformation

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Luis Gerardo Trujillo-Franco ◽  
Gerardo Silva-Navarro ◽  
Francisco Beltran-Carbajal
Keyword(s):  
Dynamic Performance ◽  
Differential Algebra ◽  
Operational Calculus ◽  
Mechanical Systems ◽  
Algebraic Approach ◽  
Parametric Identification ◽  
Hilbert Transformation ◽  
Orthogonal Functions ◽  
Matrix Operations ◽  
Specific Operating Condition

A novel algebraic scheme for parameters’ identification of a class of nonlinear vibrating mechanical systems is introduced. A nonlinearity index based on the Hilbert transformation is applied as an effective criterion to determine whether the system is dominantly linear or nonlinear for a specific operating condition. The online algebraic identification is then performed to compute parameters of mass and damping, as well as linear and nonlinear stiffness. The proposed algebraic parametric identification techniques are based on operational calculus of Mikusiński and differential algebra. In addition, we propose the combination of the introduced algebraic approach with signals approximation via orthogonal functions to get a suitable technique to be applied in embedded systems, as a digital signals’ processing routine based on matrix operations. A satisfactory dynamic performance of the proposed approach is proved and validated by experimental case studies to estimate significant parameters on the mechanical systems. The presented online identification approach can be extended to estimate parameters for a wide class of nonlinear oscillating electric systems that can be mathematically modelled by the Duffing equation.

A fast Fuel Cell Parametric Identification approach based on Machine Learning Inverse Models

Energy ◽  
2021 ◽  
pp. 122140
Author(s):  
Antonio Guarino ◽  
Riccardo Trinchero ◽  
Flavio Canavero ◽  
Giovanni Spagnuolo
Keyword(s):  
Machine Learning ◽  
Fuel Cell ◽  
Parametric Identification ◽  
Inverse Models ◽  
Identification Approach

scholarly journals On calculation of recursive M- and GM-estimates in LQG control systems

2008 ◽  
Vol 48 ◽  
Author(s):  
Rimantas Pupeikis
Keyword(s):  
Maximum Likelihood ◽  
Linear Time ◽  
Parametric Identification ◽  
Parameter Estimates ◽  
Linear Quadratic ◽  
Unknown Parameters ◽  
Linear Time Invariant ◽  
Identification Approach ◽  
Recursive Techniques ◽  
Time Invariant

The aim of the given paper is development of a parametric identification approach for a closedloop system when the parameters of a discrete-time linear time-invariant (LTI) dynamic system as well as that of LQG (Linear Quadratic Gaussian) controller are not known and ought to be calculated. The recursive techniques based on an the maximum likelihood(M) and generalized maximum likelihood(GM) estimator algorithms are applied here in the calculation of the system as well as noise filter parameters. Afterwards, the recursive parameter estimates are used in each current iteration to determine unknown parameters of the LQG-controller, too. The results of numerical simulation by computer are discussed.

scholarly journals Theoretical and Numerical Experiences on a Test Rig for Active Vibration Control of Mechanical Systems with Moving Constraints

2004 ◽  
Vol 11 (3-4) ◽  
pp. 187-197
Author(s):  
M. Rinchi ◽  
E. Gambini
Keyword(s):  
Vibration Control ◽  
Active Vibration Control ◽  
Mechanical Systems ◽  
Parametric Identification ◽  
Ball Screw ◽  
Test Rig ◽  
Design Data ◽  
Control Techniques ◽  
Active Vibration ◽  
Time Invariant

Active control of vibrations in mechanical systems has recently benefited of the remarkable development of robust control techniques. These control techniques are able to guarantee performances in spite of unavoidable modeling errors. They have been successfully codified and implemented for vibrating structures whose uncertain parameters could be assumed to be time-invariant. Unfortunately a wide class of mechanical systems, such as machine tools with carriage motion realized by a ball-screw, are characterized by time varying modal parameters. The focus of this paper is on modeling and controlling the vibrations of such systems. A test rig for active vibration control is presented. An analytical model of the test rig is synthesized starting by design data. Through experimental modal analysis, parametric identification and updating procedures, the model has been refined and a control system has been synthesized.

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