Simulant study about input/output characterization of highly nonlinear multivariable systems

2011 ◽  
Author(s):  
Zi-cai Zhan
Keyword(s):  
Multivariable Systems ◽  
Input Output ◽  
Highly Nonlinear

scholarly journals Graphical user interface for input output characterization of single variable and multivariable highly nonlinear systems

2017 ◽  
Vol 108 ◽  
pp. 10005
Author(s):  
M. D. Shahrukh Adnan Khan ◽  
Sharsad Kara Kuni ◽  
G. K. M. Sadikul Amin ◽  
Mukul Agarwal
Keyword(s):  
User Interface ◽  
Nonlinear Systems ◽  
Graphical User Interface ◽  
Single Variable ◽  
Input Output ◽  
Highly Nonlinear

scholarly journals Visco-Hyperelastic Characterization of the Equine Immature Zona Pellucida

Materials ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1223
Author(s):  
Elisa Ficarella ◽  
Mohammad Minooei ◽  
Lorenzo Santoro ◽  
Elisabetta Toma ◽  
Bartolomeo Trentadue ◽  
...  
Keyword(s):  
Zona Pellucida ◽  
Soft Matter ◽  
Mechanical Response ◽  
Mechanical Characterization ◽  
Nonlinear Material ◽  
Prony Series ◽  
Critical Comparison ◽  
Highly Nonlinear ◽  
Good Agreement

This article presents a very detailed study on the mechanical characterization of a highly nonlinear material, the immature equine zona pellucida (ZP) membrane. The ZP is modeled as a visco-hyperelastic soft matter. The Arruda–Boyce constitutive equation and the two-term Prony series are identified as the most suitable models for describing the hyperelastic and viscous components, respectively, of the ZP’s mechanical response. Material properties are identified via inverse analysis based on nonlinear optimization which fits nanoindentation curves recorded at different rates. The suitability of the proposed approach is fully demonstrated by the very good agreement between AFM data and numerically reconstructed force–indentation curves. A critical comparison of mechanical behavior of two immature ZP membranes (i.e., equine and porcine ZPs) is also carried out considering the information on the structure of these materials available from electron microscopy investigations documented in the literature.

scholarly journals On the characterization of the Duhem hysteresis operator with clockwise input–output dynamics

2013 ◽  
Vol 62 (3) ◽  
pp. 286-293 ◽  
Author(s):  
Ruiyue Ouyang ◽  
Vincent Andrieu ◽  
Bayu Jayawardhana
Keyword(s):  
Input Output ◽  
Hysteresis Operator

scholarly journals Stability of time-delay systems via Lyapunov functions

2002 ◽  
Vol 8 (3) ◽  
pp. 197-205 ◽  
Author(s):  
Carlos F. Alastruey ◽  
Manuel de la Sen
Keyword(s):  
Lyapunov Function ◽  
Lyapunov Functions ◽  
A Priori ◽  
Original System ◽  
Delay Systems ◽  
Multivariable Systems ◽  
Time Delay Systems ◽  
Input Output ◽  
Practical Applications ◽  
System A

In this paper, a Lyapunov function candidate is introduced for multivariable systems with inner delays, without assuminga prioristability for the nondelayed subsystem. By using this Lyapunov function, a controller is deduced. Such a controller utilizes an input–output description of the original system, a circumstance that facilitates practical applications of the proposed approach.

scholarly journals Application of Kalman Filtering Methods to Online Real-Time Structural Identification: A Comparison Study

2016 ◽  
Vol 16 (06) ◽  
pp. 1550016 ◽  
Author(s):  
Mohsen Askari ◽  
Jianchun Li ◽  
Bijan Samali
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
Unscented Kalman Filter ◽  
Structural Parameters ◽  
Measurement Data ◽  
Linear Structure ◽  
Structural Identification ◽  
Input Output ◽  
Output Measurement ◽  
Highly Nonlinear

System identification refers to the process of building or improving mathematical models of dynamical systems from the observed experimental input–output data. In the area of civil engineering, the estimation of the integrity of a structure under dynamic loadings and during service condition has become a challenge for the engineering community. Therefore, there has been a great deal of attention paid to online and real-time structural identification, especially when input–output measurement data are contaminated by high-level noise. Among real-time identification methods, one of the most successful and widely used algorithms for estimation of system states and parameters is the Kalman filter and its various nonlinear extensions such as extended Kalman filter (EKF), Iterated EKF (IEKF), the recently developed unscented Kalman filter (UKF) and Iterated UKF (IUKF). In this paper, an investigation has been carried out on the aforementioned techniques for their effectiveness and efficiencies through a highly nonlinear single degree of freedom (SDOF) structure as well as a two-storey linear structure. Although IEKF is an improved version of EKF, results show that IUKF generally produces better results in terms of structural parameters and state estimation than UKF and IEKF. Also IUKF is more robust to noise levels compared to the other approaches.

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