Structural real time control using fluid magnetorheologic damper

In the last decades there was a great development in the study of control systems to attenuate the harmful effect of natural events in great structures, as buildings and bridges. Magnetorheological fluid (MR), that is an intelligent material, has been considered in many proposals of project for these controllers. This work presents the controller design using feedback of states through LMI (Linear Matrix Inequalities) approach. The experimental test were carried out in a structure with two degrees of freedom with a connected shock absorber MR. Experimental tests were realized in order to specify the features of this semi-active controller. In this case, there exist states that are not measurable, so the feedback of the states involves the project of an estimator. The coupling of the MR damper causes a variation in dynamics properties, so an identification methods, based on experimental input/output signal was used to compare with the numerical application. The identification method of Prediction Error Methods - (PEM) was used to find the physical characteristics of the system through realization in modal space of states. This proposal allows the project of a semi-active control, where the main characteristic is the possibility of the variation of the damping coefficient.

A non-ideal portal frame energy harvester controlled using a pendulum

A model of energy harvester based on a simple portal frame structure is presented. The system is considered to be non-ideal system (NIS) due to interaction with the energy source, a DC motor with limited power supply and the system structure. The nonlinearities present in the piezoelectric material are considered in the piezoelectric coupling mathematical model. The system is a bi-stable Duffing oscillator presenting a chaotic behavior. Analyzing the average power variation, and bifurcation diagrams, the value of the control variable that optimizes power or average value that stabilizes the chaotic system in the periodic orbit is determined. The control sensitivity is determined to parametric errors in the damping and stiffness parameters of the portal frame. The proposed passive control technique uses a simple pendulum to tuned to the vibration of the structure to improve the energy harvesting. The results show that with the implementation of the control strategy it is possible to eliminate the need for active or semi active control, usually more complex. The control also provides a way to regulate the energy captured to a desired operating frequency. © 2013 EDP Sciences and Springer.

Controle com Estrutura Variável e Modos Deslizantes Aplicado em Sistema de Suspensão Ativa

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Sistemas dinâmicos com amortecedores ativos controlados por atuadores piezelétricos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Projetos de controle discreto com modos deslizantes para sistemas sujeitos a atraso no controle

Pós-graduação em Engenharia Elétrica - FEIS

Aplicação de controle com modos deslizantes em sistemas com atraso na aquisição de dados

Pós-graduação em Engenharia Elétrica - FEIS

Análise da robustez e aplicações de controle com modos deslizantes em sistemas incertos com atraso no controle

Pós-graduação em Engenharia Elétrica - FEIS

Otimizando vibrações sísmicas em estruturas através de controles híbridos

Pós-graduação em Engenharia Mecânica - FEIS

Controle das propriedades dinâmicas de sistemas mecânicos através da utilização de molas inteligentes

Pós-graduação em Engenharia Mecânica - FEIS

STRUCTURAL CONTROL OF A SMALL-SCALE TEST-BED SHAKER STRUCTURE USING A SPONGE-TYPE MAGNETO-RHEOLOGICAL FLUID DAMPER

Semi-active damping devices have been shown to be effective in mitigating unwanted vibrations in civil structures. These devices impart force indirectly through real-time alterations to structural properties. Simulating the complex behavior of these devices for laboratory-scale experiments is a major challenge. Commercial devices for seismic applications typically operate in the 2-10 kN range; this force is too high for small-scale testing applications where requirements typically range from 0-10 N. Several challenges must be overcome to produce damping forces at this level. In this study, a small-scale magneto-rheological (MR) damper utilizing a fluid absorbent metal foam matrix is developed and tested to accomplish this goal. This matrix allows magneto-rheological (MR) fluid to be extracted upon magnetic excitation in order to produce MR-fluid shear stresses and viscosity effects between an electromagnetic piston, the foam, and the damper housing. Dampers for uniaxial seismic excitation are traditionally positioned in the horizontal orientation allowing MR-fluid to gather in the lower part of the damper housing when partially filled. Thus, the absorbent matrix is placed in the bottom of the housing relieving the need to fill the entire device with MR-fluid, a practice that requires seals that add significant unwanted friction to the desired low-force device. The damper, once constructed, can be used in feedback control applications to reduce seismic vibrations and to test structural control algorithms and wireless command devices. To validate this device, a parametric study was performed utilizing force and acceleration measurements to characterize damper performance and controllability for this actuator. A discussion of the results is presented to demonstrate the attainment of the damper design objectives.

Vibration reduction for vision systems on board unmanned aerial vehicles using a neuro-fuzzy controller

In this paper, an intelligent control approach based on neuro-fuzzy systems performance is presented, with the objective of counteracting the vibrations that affect the low-cost vision platform onboard an unmanned aerial system of rotating nature. A scaled dynamical model of a helicopter is used to simulate vibrations on its fuselage. The impact of these vibrations on the low-cost vision system will be assessed and an intelligent control approach will be derived in order to reduce its detrimental influence. Different trials that consider a neuro-fuzzy approach as a fundamental part of an intelligent semi-active control strategy have been carried out. Satisfactory results have been achieved compared to those obtained by means of vibration reduction passive techniques.

A influência do amortecimento viscoelástico na estabilidade aeroelástica de painéis aeronáuticos

Since the creation of supersonic vehicles, during the Second World War, the engineers have given special attention to the interaction between the aerodynamic efforts and the structures of the aircrafts due to a highly destructive phenomenon called flutter in aeronautical panel. Flutter in aeronautical panels is a self-excited aeroelastic phenomenon, which can occurs during supersonic flights due to dynamic instability of inertia, elastic and aerodynamic forces of the system. In the flutter condition, when the critical aerodynamic pressure is reached, the vibration amplitudes of the panel become dynamically unstable and increase exponentially with time, affecting significantly the fatigue life of the existing aeronautical components. Thus, in this paper, the interest is to investigate the possibility of reducing the effects of the supersonic aeroelastic instability of rectangular plates by applying passive constrained viscoelastic layers. The rationale for such study is the fact that as the addition of viscoelastic materials provides decreased vibration amplitudes it becomes important to quantify the suppression of plate flutter coalescence modes that can be obtained. Moreover, despite the fact that much research on the suppression of panel flutter has been carried out by using passive, semi-active and active control techniques, very few of them are adapted to deal with the problem of estimating the flutter speeds of viscoelastic systems, since they must conveniently account for the frequency- and temperature-dependent behavior of the viscoelastic material. In this context, two different model of viscoelastic material are developed and applied to the model of sandwich plate by using finite elements. After the presentation of the theoretical foundations of the methodology, the description of a numerical study on the flutter analysis of a three-layer sandwich plate is addressed.

Brain emotional learning based control of a SDOF structural system with a MR damper

This paper describes the application of a Brain Emotional Learning (BEL) controller to improve the response of a SDOF structural system under an earthquake excitation using a magnetorheological (MR) damper. The main goal is to study the performance of a BEL based semi-active control system to generate the control signal for a MR damper. The proposed approach consists of a two controllers: a primary controller based on a BEL algorithm that determines the desired damping force from the system response and a secondary controller that modifies the input current to the MR damper to generate a reference damping force. A parametric model of the damper is used to predict the damping force based on the piston motion and also the current input. A Simulink model of the structural system is developed to analyze the effectiveness of the semi-active controller. Finally, the numerical results are presented and discussed.

Combined active and semi-supervised learning using particle walking temporal dynamicscombined active and semi-supervised learning using particle walking temporal dynamics

Both Semi-Supervised Leaning and Active Learning are techniques used when unlabeled data is abundant, but the process of labeling them is expensive and/or time consuming. In this paper, those two machine learning techniques are combined into a single nature-inspired method. It features particles walking on a network built from the data set, using a unique random-greedy rule to select neighbors to visit. The particles, which have both competitive and cooperative behavior, are created on the network as the result of label queries. They may be created as the algorithm executes and only nodes affected by the new particles have to be updated. Therefore, it saves execution time compared to traditional active learning frameworks, in which the learning algorithm has to be executed several times. The data items to be queried are select based on information extracted from the nodes and particles temporal dynamics. Two different rules for queries are explored in this paper, one of them is based on querying by uncertainty approaches and the other is based on data and labeled nodes distribution. Each of them may perform better than the other according to some data sets peculiarities. Experimental results on some real-world data sets are provided, and the proposed method outperforms the semi-supervised learning method, from which it is derived, in all of them.

Application of active and passive suspension techniques to improve high speed ground vehicle performance - phase II. Final report.

Transportation Department, Office of University Research, Washington, D.C.