Generalized frequency response of the nonlinear second order system

2011 ◽  
Author(s):  
Ashraf Omran ◽  
Brett Newman
Keyword(s):  
Frequency Response ◽  
Second Order ◽  
Order System

Identifying parametric variation in second-order system from frequency response measurement

2016 ◽  
Vol 24 (5) ◽  
pp. 879-891 ◽  
Author(s):  
A Hegde ◽  
J Tang
Keyword(s):  
Frequency Response ◽  
Parametric Identification ◽  
Second Order ◽  
Order System ◽  
Model Parameters ◽  
Order Model ◽  
Response Measurement ◽  
Electrical Systems ◽  
Angle Measurements ◽  
Second Order Model

Fundamentally, second-order model is the foundation of describing the dynamic characteristics of many mechanical and electrical systems. This paper investigates a parametric identification scheme for single degree-of-freedom second-order model in which the model parameters are subject to normal variation. By utilizing frequency response magnitude and phase angle measurements, we construct a linear-in-the-parameters model and build a related maximum likelihood estimator for both parametric means as well as variances. The validity of the approach is demonstrated through a collection of case analyses, and the results show considerable levels of accuracy in the presence of sufficient data.

Frequency response of human soleus muscle

1976 ◽  
Vol 39 (4) ◽  
pp. 788-793 ◽  
Author(s):  
P. Bawa ◽  
R. B. Stein
Keyword(s):  
Frequency Response ◽  
Natural Frequency ◽  
Soleus Muscle ◽  
Damping Ratio ◽  
Low Frequency ◽  
Second Order ◽  
Order System ◽  
Pass Filter ◽  
Stimulus Pulse ◽  
Low Pass Filter

1. The properties of human soleus muscle were studied by systems analysis. Single stimulus pulses and random stimulus pulse trains were applied to a branch of the nerve to soleus muscle and the resultant tension fluctuations were recorded. 2. The frequency-response function between stimulus pulses and tension conforms to that of a second-order, low-pass filter. The parameters of the second-order system, low frequency gain, natural frequency, and damping ratio, varied systematically with the angle of the ankle. As the ankle was flexed (the length of the muscle was increased), the low frequency gain increased, the natural frequency decreased, and the damping ratio was unaffected or increased slightly. 3. These results are discussed in relation to the twitch responses of human soleus muscles and the responses previously observed in cat muscles.

Natural Forcing Functions in Nonlinear Systems

1958 ◽  
Vol 25 (3) ◽  
pp. 352-356
Author(s):  
T. J. Harvey
Keyword(s):  
Frequency Response ◽  
Maximum Amplitude ◽  
Second Order ◽  
Point Of View ◽  
Order System ◽  
Nonlinear Frequency ◽  
Restoring Force ◽  
Forcing Function ◽  
Special Cases ◽  
Forcing Functions

Abstract The response of nonlinear, second-order systems is examined from a new point of view which greatly simplifies presentation of the usual frequency-response diagrams. The use of “natural” forcing functions results in a general equation relating the maximum amplitude of the applied force to the maximum amplitude of the restoring force. The relationship is found to be a function of the ratio of the period of free oscillation to the period of the forcing function. The results apply for any second-order system without damping and with a nonlinear (or linear) restoring force. The special cases of a linear system and of Duffing’s equation are considered to illustrate similarities as well as differences between treatment of linear and nonlinear frequency-response problems.

scholarly journals Search Patterns Based on Trajectories Extracted from the Response of Second-Order Systems

2021 ◽  
Vol 11 (8) ◽  
pp. 3430
Author(s):  
Erik Cuevas ◽  
Héctor Becerra ◽  
Héctor Escobar ◽  
Alberto Luque-Chang ◽  
Marco Pérez ◽  
...  
Keyword(s):  
Convergence Rates ◽  
Optimization Problems ◽  
Search Space ◽  
Second Order ◽  
Order System ◽  
Search Patterns ◽  
Multiple Behaviors ◽  
Complex Optimization ◽  
Second Order Systems ◽  
Order Algorithm

Recently, several new metaheuristic schemes have been introduced in the literature. Although all these approaches consider very different phenomena as metaphors, the search patterns used to explore the search space are very similar. On the other hand, second-order systems are models that present different temporal behaviors depending on the value of their parameters. Such temporal behaviors can be conceived as search patterns with multiple behaviors and simple configurations. In this paper, a set of new search patterns are introduced to explore the search space efficiently. They emulate the response of a second-order system. The proposed set of search patterns have been integrated as a complete search strategy, called Second-Order Algorithm (SOA), to obtain the global solution of complex optimization problems. To analyze the performance of the proposed scheme, it has been compared in a set of representative optimization problems, including multimodal, unimodal, and hybrid benchmark formulations. Numerical results demonstrate that the proposed SOA method exhibits remarkable performance in terms of accuracy and high convergence rates.

A low-order system frequency response model

1990 ◽  
Vol 5 (3) ◽  
pp. 720-729 ◽  
Author(s):  
P.M. Anderson ◽  
M. Mirheydar
Keyword(s):  
Frequency Response ◽  
Order System ◽  
Response Model ◽  
System Frequency ◽  
Low Order

Development of a Second-Order System for Rapid Estimation of Maximum Brain Strain

2018 ◽  
Vol 47 (9) ◽  
pp. 1971-1981 ◽  
Author(s):  
Lee F. Gabler ◽  
Jeff R. Crandall ◽  
Matthew B. Panzer
Keyword(s):  
Second Order ◽  
Order System ◽  
Rapid Estimation
Sign in / Sign up

Export Citation Format

Share Document