Introduction to Experimental Non-linear Dynamics A Case Study in Mechanical Vibration

2001 ◽  
Vol 23 (8) ◽  
pp. 1043
Author(s):  
John S Owen
2003 ◽  
Vol 17 (2-3) ◽  
pp. 545-555 ◽  
Author(s):  
P. Arena ◽  
S. Fazzino ◽  
L. Fortuna ◽  
P. Maniscalco

Author(s):  
C E N Mazzilli ◽  
G C Monticelli ◽  
N A Galan Neto

It is largely accepted that non-linear modes of vibration may be particularly suitable for obtaining ‘reduced-order’ models in non-linear dynamics, for their ability to grasp the essential qualitative system information that a much larger number of linear modes are required to. Previous work by the first author on ‘reduced-order’ modelling in non-linear dynamics did not account for the velocity contents within non-linear modes. For many systems, this simplifying assumption does not, in fact, spoil the quality of the ‘reduced-order’ model. Nevertheless, it is not to be generally taken for granted. In this article, a generalised procedure for ‘reduced-order’ modelling in non-linear dynamics that uses the full displacement and velocity contents of non-linear modes is addressed and illustrated. Two case studies are presented and conclusions regarding the relevance of the velocity contents are drawn. Comparison between non-linear dynamic responses of finite-element and ‘reduced-order’ models under different load conditions is made. For both external and parametric resonances, a remarkable agreement between them was achieved, provided the velocity contents within the non-linear modes are retained. In the second case study, damping is essential to help the system settling down in a post-critical periodic attractor, otherwise wave propagation and reflection will have an enduring effect.


2002 ◽  
Vol 16 (6) ◽  
pp. 555-561 ◽  
Author(s):  
M. S. Lesniak ◽  
R. E. Clatterbuck ◽  
D. Rigamonti ◽  
M. A. Williams

2017 ◽  
Author(s):  
Giovanni Antonio Chirilli
Keyword(s):  

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Akshaykumar Naregalkar ◽  
Subbulekshmi Durairaj

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.


Author(s):  
Aly-Joy Ulusoy ◽  
Filippo Pecci ◽  
Ivan Stoianov

AbstractThis manuscript investigates the design-for-control (DfC) problem of minimizing pressure induced leakage and maximizing resilience in existing water distribution networks. The problem consists in simultaneously selecting locations for the installation of new valves and/or pipes, and optimizing valve control settings. This results in a challenging optimization problem belonging to the class of non-convex bi-objective mixed-integer non-linear programs (BOMINLP). In this manuscript, we propose and investigate a method to approximate the non-dominated set of the DfC problem with guarantees of global non-dominance. The BOMINLP is first scalarized using the method of $$\epsilon $$ ϵ -constraints. Feasible solutions with global optimality bounds are then computed for the resulting sequence of single-objective mixed-integer non-linear programs, using a tailored spatial branch-and-bound (sBB) method. In particular, we propose an equivalent reformulation of the non-linear resilience objective function to enable the computation of global optimality bounds. We show that our approach returns a set of potentially non-dominated solutions along with guarantees of their non-dominance in the form of a superset of the true non-dominated set of the BOMINLP. Finally, we evaluate the method on two case study networks and show that the tailored sBB method outperforms state-of-the-art global optimization solvers.


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