A co-rotational element/time-integration strategy for non-linear dynamics

1994 ◽  
Vol 37 (11) ◽  
pp. 1897-1913 ◽  
Author(s):  
M. A. Crisfield ◽  
J. Shi
Keyword(s):  
Time Integration ◽  
Linear Dynamics ◽  
Integration Strategy ◽  
Rotational Element ◽  
Non Linear

scholarly journals Application of a Novel Picard-Type Time-Integration Technique to the Linear and Non-Linear Dynamics of Mechanical Structures: An Exemplary Study

2021 ◽  
Vol 11 (9) ◽  
pp. 3742
Author(s):  
Evgenii Oborin ◽  
Hans Irschik
Keyword(s):  
Time Integration ◽  
Harmonic Excitation ◽  
Free Vibrations ◽  
Observation Time ◽  
Double Pendulum ◽  
Integration Technique ◽  
Linear Dynamics ◽  
Non Linear ◽  
Linear Vibrations ◽  
Numerical Time Integration

Applications of a novel time-integration technique to the non-linear and linear dynamics of mechanical structures are presented, using an extended Picard-type iteration. Explicit discrete-mechanics approximations are taken as starting guess for the iteration. Iteration and necessary symbolic operations need to be performed only before time-stepping procedure starts. In a previous investigation, we demonstrated computational advantages for free vibrations of a hanging pendulum. In the present paper, we first study forced non-linear vibrations of a tower-like mechanical structure, modeled by a standing pendulum with a non-linear restoring moment, due to harmonic excitation in primary parametric vertical resonance, and due to excitation recordings from a real earthquake. Our technique is realized in the symbolic computer languages Mathematica and Maple, and outcomes are successfully compared against the numerical time-integration tool NDSolve of Mathematica. For out method, substantially smaller computation times, smaller also than the real observation time, are found on a standard computer. We finally present the application to free vibrations of a hanging double pendulum. Excellent accuracy with respect to the exact solution is found for comparatively large observation periods.

Low pressure hydrocephalus and ventriculomegaly: hysteresis, non-linear dynamics, and the benefits of CSF diversion

2002 ◽  
Vol 16 (6) ◽  
pp. 555-561 ◽  
Author(s):  
M. S. Lesniak ◽  
R. E. Clatterbuck ◽  
D. Rigamonti ◽  
M. A. Williams
Keyword(s):  
Low Pressure ◽  
Linear Dynamics ◽  
Non Linear ◽  
Csf Diversion

Non-linear dynamics in DIS at NLO

2017 ◽  
Author(s):  
Giovanni Antonio Chirilli
Keyword(s):  
Linear Dynamics ◽  
Non Linear

A novel LSSVM-L Hammerstein model structure for system identification and nonlinear model predictive control of CSTR servo and regulatory control

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Akshaykumar Naregalkar ◽  
Subbulekshmi Durairaj
Keyword(s):  
Linear System ◽  
Regulatory Control ◽  
Hammerstein Model ◽  
Support Vector ◽  
Model Structure ◽  
Linear Dynamics ◽  
Vector Machines ◽  
Non Linear ◽  
Laguerre Filters ◽  
Non Linear System

Abstract A continuous stirred tank reactor (CSTR) servo and the regulatory control problem are challenging because of their highly non-linear nature, frequent changes in operating points, and frequent disturbances. System identification is one of the important steps in the CSTR model-based control design. In earlier work, a non-linear system model comprises a linear subsystem followed by static nonlinearities and represented with Laguerre filters followed by the LSSVM (least squares support vector machines). This model structure solves linear dynamics first and then associated nonlinearities. Unlike earlier works, the proposed LSSVM-L (least squares support vector machines and Laguerre filters) Hammerstein model structure solves the nonlinearities associated with the non-linear system first and then linear dynamics. Thus, the proposed Hammerstein’s model structure deals with the nonlinearities before affecting the entire system, decreasing the model complexity and providing a simple model structure. This new Hammerstein model is stable, precise, and simple to implement and provides the CSTR model with a good model fit%. Simulation studies illustrate the benefit and effectiveness of the proposed LSSVM-L Hammerstein model and its efficacy as a non-linear model predictive controller for the servo and regulatory control problem.

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