904 resultados para Feedback Control Loop


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The present work investigates the nonlinear response of a half-car model. The disturbances of the road are assumed to be sinusoidal. After constructing the bifurcation diagram, we use the 0-1 test to identify chaotic motions. The main objective of this study is to eliminate chaotic behavior of the chassis and reduce its vibrations. To accomplish this, a semi-active vehicle suspension control system, using magneto-rheological dampers, is proposed. The proposed semi-active control strategy consists of two nonlinear control laws: a feedforward control, and a feedback control. They are obtained by considering the SDRE (State Dependent Riccati Equation) control, where the control parameter is the voltage applied to the coils of the magneto-rheological dampers. Numerical results show that the proposed control method is effective in significantly reducing of the chassis vibration, increasing, therefore, passenger comfort.

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During the last 30 years the Atomic Force Microscopy became the most powerful tool for surface probing in atomic scale. The Tapping-Mode Atomic Force Microscope is used to generate high quality accurate images of the samples surface. However, in this mode of operation the microcantilever frequently presents chaotic motion due to the nonlinear characteristics of the tip-sample forces interactions, degrading the image quality. This kind of irregular motion must be avoided by the control system. In this work, the tip-sample interaction is modelled considering the Lennard-Jones potentials and the two-term Galerkin aproximation. Additionally, the State Dependent Ricatti Equation and Time-Delayed Feedback Control techniques are used in order to force the Tapping-Mode Atomic Force Microscope system motion to a periodic orbit, preventing the microcantilever chaotic motion

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Micro-electromechanical systems (MEMS) are micro scale devices that are able to convert electrical energy into mechanical energy or vice versa. In this paper, the mathematical model of an electronic circuit of a resonant MEMS mass sensor, with time-periodic parametric excitation, was analyzed and controlled by Chebyshev polynomial expansion of the Picard interaction and Lyapunov-Floquet transformation, and by Optimal Linear Feedback Control (OLFC). Both controls consider the union of feedback and feedforward controls. The feedback control obtained by Picard interaction and Lyapunov-Floquet transformation is the first strategy and the optimal control theory the second strategy. Numerical simulations show the efficiency of the two control methods, as well as the sensitivity of each control strategy to parametric errors. Without parametric errors, both control strategies were effective in maintaining the system in the desired orbit. On the other hand, in the presence of parametric errors, the OLFC technique was more robust.

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Fluctuation-dissipation theorems can be used to predict characteristics of noise from characteristics of the macroscopic response of a system. In the case of gene networks, feedback control determines the "network rigidity," defined as resistance to slow external changes. We propose an effective Fokker-Planck equation that relates gene expression noise to topology and to time scales of the gene network. We distinguish between two situations referred to as normal and inverted time hierarchies. The noise can be buffered by network feedback in the first situation, whereas it can be topology independent in the latter.

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DNA damage induced by ultraviolet (UV) radiation can be removed by nucleotide excision repair through two sub-pathways, one general (GGR) and the other specific for transcribed DNA (TCR), and the processing of unrepaired lesions trigger signals that may lead to cell death. These signals involve the tumor suppressor p53 protein, a central regulator of cell responses to DNA damage, and the E3 ubiquitin ligase Mdm2, that forms a feedback regulatory loop with p53. The involvement of cell cycle and transcription on the signaling to apoptosis was investigated in UVB-irradiated synchronized, DNA repair proficient, CS-B (TCR-deficient) and XP-C (GGR-deficient) primary human fibroblasts. Cells were irradiated in the G1 phase of the cell cycle, with two doses with equivalent levels of apoptosis (low and high), defined for each cell line. In the three cell lines, the low doses of UVB caused only a transient delay in progression to the S phase, whereas the high doses induced permanent cell cycle arrest. However, while accumulation of Mdm2 correlated well with the recovery from transcription inhibition at the low doses for normal and CS-B fibroblasts, for XP-C cells this protein was shown to be accumulated even at UVB doses that induced high levels of apoptosis. Thus, UVB-induced accumulation of Mdm2 is critical for counteracting p53 activation and apoptosis avoidance, but its effect is limited due to transcription inhibition. However, in the case of XP-C cells, an excess of unrepaired DNA damage would be sufficient to block S phase progression, which would signal to apoptosis, independent of Mdm2 accumulation. The data clearly discriminate DNA damage signals that lead to cell death, depending on the presence of UVB-induced DNA damage in replicating or transcribing regions.

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[EN] This project briefly analyzes the scope and applications of Industrial Robotics, as well as the importance that this technical discipline has gained in the past decades. In addition, it proposes a modern platform to assist in teaching this discipline in colleges and universities. This new educational platform for the teaching of Industrial Robotics is based on the robotic systems from Rhino Robotics Ltd., using the existing robotic arms and replacing the control electronics by a newer, modern and yet backwards-compatible controller. In addition to the controller, this platform also provides new, up-to-date software utilities that are more intuitive than those provided with the old system. The work to be done consists essentially in receiving commands from a personal computer which the controller must interpret in order to control the motors of the robotic arm. The controller itself will be implemented as an embedded system based on microcontrollers. This requires the implementation of a communication protocol between the personal computer and the microcontroller, the design of a command interpreter, the design of the electronics for motor control using PWM and H-bridges, and the implementation of control techniques (more precisely, PID control). Hence, this project combines software and hardware design and integration techniques with motor control techniques and feedback control methods from Control Engineering, along with the kinematic analysis of the Rhino XR-4 robotic arm. 

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The present thesis focuses on the problem of robust output regulation for minimum phase nonlinear systems by means of identification techniques. Given a controlled plant and an exosystem (an autonomous system that generates eventual references or disturbances), the control goal is to design a proper regulator able to process the only measure available, i.e the error/output variable, in order to make it asymptotically vanishing. In this context, such a regulator can be designed following the well known “internal model principle” that states how it is possible to achieve the regulation objective by embedding a replica of the exosystem model in the controller structure. The main problem shows up when the exosystem model is affected by parametric or structural uncertainties, in this case, it is not possible to reproduce the exact behavior of the exogenous system in the regulator and then, it is not possible to achieve the control goal. In this work, the idea is to find a solution to the problem trying to develop a general framework in which coexist both a standard regulator and an estimator able to guarantee (when possible) the best estimate of all uncertainties present in the exosystem in order to give “robustness” to the overall control loop.

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Diaphragmatic electrical activity (EA(di)), reflecting respiratory drive, and its feedback control might be impaired in critical illness-associated polyneuromyopathy (CIPM). We aimed to evaluate whether titration and prolonged application of neurally adjusted ventilatory assist (NAVA), which delivers pressure (P (aw)) in proportion to EA(di), is feasible in CIPM patients.

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Ventricular assist devices (VADs) are blood pumps that offer an option to support the circulation of patients with severe heart failure. Since a failing heart has a remaining pump function, its interaction with the VAD influences the hemodynamics. Ideally, the heart's action is taken into account for actuating the device such that the device is synchronized to the natural cardiac cycle. To realize this in practice, a reliable real-time algorithm for the automatic synchronization of the VAD to the heart rate is required. This paper defines the tasks such an algorithm needs to fulfill: the automatic detection of irregular heart beats and the feedback control of the phase shift between the systolic phases of the heart and the assist device. We demonstrate a possible solution to these problems and analyze its performance in two steps. First, the algorithm is tested using the MIT-BIH arrhythmia database. Second, the algorithm is implemented in a controller for a pulsatile and a continuous-flow VAD. These devices are connected to a hybrid mock circulation where three test scenarios are evaluated. The proposed algorithm ensures a reliable synchronization of the VAD to the heart cycle, while being insensitive to irregularities in the heart rate.

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Expression of the structural genes for the anthrax toxin proteins is coordinately controlled by host-related signals such as elevated CO2 , and the trans-acting positive regulator, AtxA. No specific binding of AtxA to the toxin gene promoters has been demonstrated and no sequence-based similarities are apparent in the promoter regions of toxin genes. We hypothesized that the toxin genes possess common structural features that are required for positive regulation. To test this hypothesis, I performed an extensive characterization of the toxin gene promoters. I determined the minimal sequences required for atxA-mediated toxin gene expression and compared these sequences for structural similarities. In silico modeling and in vitro experiments indicated significant curvature within these regions. Random mutagenesis revealed that point mutations associated with reduced transcriptional activity, mostly mapped to areas of high curvature. This work enabled the identification of two potential cis-acting elements implicated in AtxA-mediated regulation of the toxin genes. In addition to the growth condition requirements and AtxA, toxin gene expression is under growth phase regulation. The transition state regulator AbrB represses atxA expression to influence toxin synthesis. Here I report that toxin gene expression also requires sigH, a gene encoding the RNA polymerase sigma factor associated with development in B. subtilis. In the well-studied B. subtilis system, σH is part of a feedback control pathway that involves AbrB and the major response regulator of sporulation initiation, Spo0A. My data indicate that in B. anthracis, regulatory relationships exist between these developmental regulators and atxA . Interestingly, during growth in toxin-inducing conditions, sigH and abrB expression deviates from that described for B. subtilis, affecting expression of the atxA gene. These findings, combined with previous observations, suggest that the steady state level of atxA expression is critical for optimal toxin gene transcription. I propose a model whereby, under toxin-inducing conditions, control of toxin gene expression is fine-tuned by the independent effects of the developmental regulators on the expression of atxA . The growth condition-dependent changes in expression of these regulators may be crucial for the correct timing and uninterrupted expression of the toxin genes during infection. ^

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Brain metastasis, which occurs in 40%-60% of patients with advanced melanoma, has led directly to death in the majority of cases. Unfortunately, little is known about the biological and molecular basis of melanoma brain metastases. In our previous study, we developed a model to study human melanoma brain metastasis and found that Stat3 activity was increased in human brain metastatic melanoma cells when compared with that in cutaneous melanoma cells. The increased activation of Stat3 is also responsible for affecting melanoma angiogenesis in vivo and melanoma cell invasion in vitro and significantly affecting the expression of bFGF, VEGF, and MMP-2 in vivo and in vitro. Interestingly, a member of a new family of cytokine-inducible inhibitors of signal transduction, termed suppressors of cytokine signaling 1 (SOCS1) was found to negatively regulate the Janus kinase signal transducer and activator of transcription (Jak/STAT) signaling cascade. Here we report that restoration of SOCS1 expression by transfecting of SOCS1-expressing vector effectively inhibited melanoma brain metastasis through inhibiting Stat3 activation and further affecting melanoma angiogenesis and melanoma cell invasion in vitro, and significantly affected the expression of vascular endothelial growth factor (VEGF) and matrix metalloproteinase-2 (MMP-2) in vitro and in vivo. In addition, we used cDNA array to compare mRNA expression in the SOCS1-transfected and vector-transfected cell lines and found some genes are tightly correlated to the restoration of SOCS1. One of them is Caveolin-1 (Cav-1). Cav-1 was reported to function as a tumor suppressor gene by several groups. Finally, the Cav-1 expression is up-regulated in SOCS1-overexpressing cell line. Further study found the regulation of Cav-1 by SOCS1 occurs through inhibiting Stat3 activation. Activated Stat3 binds directly to Cav-1 promoter and the Cav-1 promoter within -575bp is essential for active Stat3 binding. My studies reveal that Stat3 activation and SOCS1 expression play important roles in melanoma metastases. Moreover, the expression between SOCS1, Stat3 and Cav-1 forms a feedback regulation loop. ^

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The runtime management of the infrastructure providing service-based systems is a complex task, up to the point where manual operation struggles to be cost effective. As the functionality is provided by a set of dynamically composed distributed services, in order to achieve a management objective multiple operations have to be applied over the distributed elements of the managed infrastructure. Moreover, the manager must cope with the highly heterogeneous characteristics and management interfaces of the runtime resources. With this in mind, this paper proposes to support the configuration and deployment of services with an automated closed control loop. The automation is enabled by the definition of a generic information model, which captures all the information relevant to the management of the services with the same abstractions, describing the runtime elements, service dependencies, and business objectives. On top of that, a technique based on satisfiability is described which automatically diagnoses the state of the managed environment and obtains the required changes for correcting it (e.g., installation, service binding, update, or configuration). The results from a set of case studies extracted from the banking domain are provided to validate the feasibility of this proposa

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Decreasing the accidents on highway and urban environments is the main motivation for the research and developing of driving assistance systems, also called ADAS (Advanced Driver Assistance Systems). In recent years, there are many applications of these systems in commercial vehicles: ABS systems, Cruise Control (CC), parking assistance and warning systems (including GPS), among others. However, the implementation of driving assistance systems on the steering wheel is more limited, because of their complexity and sensitivity. This paper is focused in the development, test and implementation of a driver assistance system for controlling the steering wheel in curve zones. This system is divided in two levels: an inner control loop which permits to execute the position and speed target, softening the action over the steering wheel, and a second control outer loop (controlling for fuzzy logic) that sends the reference to the inner loop according the environment and vehicle conditions. The tests have been done in different curves and speeds. The system has been proved in a commercial vehicle with satisfactory results.