Abstract The present study develops and applies a neuro-fuzzy modal vibration control of smart laminated composite structures with piezoelectric layers via Mixed theory. Differently from previous studies, the composite structures in this paper are modeled via the Mixed Theory using the High-order Shear Deformation Theory (HSDT) theory. The Mixed Theory adopts a single layer when representing the mechanical displacement field, through HSDT theory, and multiple layers (Layerwise theory) for the electrical degrees of freedom. The Mixed Theory is computationally implemented in the Matlab® software using a plate-type element called Serendipity. Moreover, a neuro-fuzzy active vibration controller is implemented to attenuate the vibration of the smart composite structures. The numerical results validate the electric-mechanical coupling adopted, showing the importance of the mixed theory in the static and dynamic modeling of slender beams and plates with piezoelectric layers. Finally, the results of the robustness analysis indicate that the neuro-fuzzy controller has benefits compared with the linear quadratic regulator.

Abstract This paper aims at analyzing the sensitivity of the structural response of flexible rotors subjected to uncertain interval parameters. The interval approach encompasses both an uncertainty and sensitivity analyses. The uncertainty analysis consists in computing the interval uncertain structural responses by using the global optimization method. The sensitivity analysis computes the normalized relative sensitivity indices that quantify the degree of importance of each uncertain interval parameter on the uncertain structural responses of the flexible rotor. The uncertain structural responses and the sensitivity of the flexible rotor subjected to interval parameters are analyzed in terms of the Frequency Response Function (FRF), orbits, Campbell diagram, and run-up operating condition. Numerical simulation results illustrate the interval approach conveyed.

Abstract The components of flexible rotors are subjected to uncertainties. The main sources of uncertainties include the variation of mechanical properties. This contribution aims at analyzing the dynamics of flexible rotors under uncertain parameters modeled as fuzzy and fuzzy random variables. The uncertainty analysis encompasses the modeling of uncertain parameters and the numerical simulation of the corresponding flexible rotor model by using an approach based on fuzzy dynamic analysis. The numerical simulation is accomplished by mapping the fuzzy parameters of the deterministic flexible rotor model. Thereby, the flexible rotor is modeled by using both the Fuzzy Finite Element Method and the Fuzzy Stochastic Finite Element Method. Numerical simulations illustrate the methodology conveyed in terms of orbits and frequency response functions subject to uncertain parameters.

AbstractThis paper is dedicated to the analyses of the effect of uncertain parameters on the dynamic behavior of a flexible rotor containing two rigid discs and supported by two fluid film bearings. A stochastic method has been extensively used to model uncertain parameters, i.e., the so-called Monte Carlo simulation. However, in the present contribution, the inherent uncertainties of the bearings' parameters (i.e. the oil viscosity as a function of the oil temperature, and the radial clearance) are modeled by using a fuzzy dynamic analysis. This alternative methodology seems to be more appropriated when the stochastic process that models the uncertainties is unknown. The analysis procedure is confined to the time domain, being generated by the envelopes of the rotor orbits and the unbalance responses obtained from a run-down operating condition. The hydrodynamic supporting forces are determined by considering a nonlinear model, which is based on the solution of the dimensionless Reynolds' equation for cylindrical and short journal bearings. This numerical study illustrates the versatility and convenience of the mentioned fuzzy approach for uncertainty analysis. The results from the stochastic analysis are also presented for comparison purposes.

Este trabalho apresenta a aplicação de técnicas de controle preditivo para rastreamento de trajetórias de um robô paralelo. A estratégia de controle preditivo generalizado (GPC), que considera o modelo dinâmico linearizado, é usada para melhorar a precisão de rastreamento das trajetórias. O controlador preditivo generalizado é robustificado devido ao ruído de medição e dinâmicas não modeladas utilizando parametrização Youla. É realizada Uma simulação do robô Orthoglide considerando as incertezas dos parâmetros geométricos e dinâmicos, ruído nos sensores e atritos para duas trajetórias diferentes. Finalmente, o controlador GPC robus-tificado e a técnica de Controle de Torque Computado (CTC) são comparadas. Os resultados das simulações mostram que o controlador GPC robustificado apresenta um melhor desempenho para altas acelerações e também reduz o efeito do ruído no sinal de controle do robô paralelo.

This paper addresses the position tracking control application of a parallel robot using predictive control techniques. A Generalized Predictive Control strategy (GPC), which considers the linear dynamic model, is used to enhance the tracking position accuracy. The robustification of GPC against measurement noise and neglected dynamics using Youla parameterization is performed. A simulation of the orthoglide robot considering uncertainties related to geometrical and dynamic parameters, sensors noise and frictions is performed on two different trajectories. Finally, it is compared the ro-bustified GPC controller with the classical Computed Torque Control (CTC). The robustified GPC controller shows a better performance for high accelerations and it also reduces the effect of the noise in the control signal of the parallel robot.