scholarly journals Resonant manifestation of intrinsic nonlinearity within electroelastic micropower generators

2010 ◽  
Vol 97 (25) ◽  
pp. 254101 ◽  
Author(s):  
Samuel C. Stanton ◽  
Alper Erturk ◽  
Brian P. Mann ◽  
Daniel J. Inman
Author(s):  
S. J. Dyke ◽  
B. F. Spencer ◽  
M. K. Sain ◽  
J. D. Carlson

Abstract In this paper, the efficacy of magnetorheological (MR) dampers for seismic protection of structures is investigated through a series of experiments in which an MR damper is used to control a three story test structure subjected to a one-dimensional earthquake motion. Because of the intrinsic nonlinearity of the MR damper, several earthquake amplitudes are considered to investigate the performance, in terms of both peak and rms responses, of this control systems over a range of loading conditions. The results indicate that the MR damper is quite effective for structural response reduction over a wide class of seismic excitations.


2018 ◽  
Vol 38 (5) ◽  
pp. 568-575 ◽  
Author(s):  
Weilin Yang ◽  
Wentao Zhang ◽  
Dezhi Xu ◽  
Wenxu Yan

Purpose Robotic arm control is challenging due to the intrinsic nonlinearity. Proportional-integral-derivative (PID) controllers prevail in many robotic arm applications. However, it is usually nontrivial to tune the parameters in a PID controller. This paper aims to propose a model-based control strategy of robotic arms. Design/methodology/approach A Takagi–Sugeno (T-S) fuzzy model, which is capable of approximating nonlinear systems, is used to describe the dynamics of a robotic arm. Model predictive control (MPC) based on the T-S fuzzy model is considered, which optimizes system performance with respect to a user-defined cost function. Findings The control gains are optimized online according to the real-time system state. Furthermore, the proposed method takes into account the input constraints. Simulations demonstrate the effectiveness of the fuzzy MPC approach. It is shown that asymptotic stability is achieved for the closed-loop control system. Originality/value The T-S fuzzy model is discussed in the modeling of robotic arm dynamics. Fuzzy MPC is used for robotic arm control, which can optimize the transient performance with respect to a user-defined criteria.


Author(s):  
Troy Shinbrot

Flow solutions in the presence of pulsation (e.g. from the heart) are developed. Bessel functions are introduced as an aside. The concepts of shocks and solitary waves (solitons) are then discussed as examples of nonlinear effects. The strategy for dealing with intrinsic nonlinearity is described in terms of mode coupling and the Korteweg–de Vries (KdV) equation.


Polymers ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 365
Author(s):  
Hyeong Yong Song ◽  
Lorenz Faust ◽  
Jinha Son ◽  
Mingeun Kim ◽  
Seung Joon Park ◽  
...  

Linear and nonlinear rheological properties of model comb polystyrenes (PS) with loosely to densely grafted architectures were measured under small and medium amplitude oscillatory shear (SAOS and MAOS) flow. This comb PS set had the same length of backbone and branches but varied in the number of branches from 3 to 120 branches. Linear viscoelastic properties of the comb PS were compared with the hierarchical model predictions. The model underpredicted zero-shear viscosity and backbone plateau modulus of densely branched comb with 60 or 120 branches because the model does not include the effect of side chain crowding. First- and third-harmonic nonlinearities reflected the hierarchy in the relaxation motion of comb structures. Notably, the low-frequency plateau values of first-harmonic MAOS moduli scaled with M w − 2 (total molecular weight), reflecting dynamic tube dilution (DTD) by relaxed branches. Relative intrinsic nonlinearity Q0 exhibited the difference between comb and bottlebrush via no low-frequency Q0 peak of bottlebrush corresponding to backbone relaxation, which is probably related to the stretched backbone conformation in bottlebrush.


Author(s):  
Fabrizio Di Mei ◽  
Davide Pierangeli ◽  
Jacopo Parravicini ◽  
Giambattista Parravicini ◽  
Aharon J. Agranat ◽  
...  

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