10 resultados para Flight control systems

em Universidade Federal do Rio Grande do Norte(UFRN)


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A self-flotator vibrational prototype electromechanical drive for treatment of oil and water emulsion or like emulsion is presented and evaluated. Oil production and refining to obtain derivatives is carried out under arrangements technically referred to as on-shore and off-shore, ie, on the continent and in the sea. In Brazil 80 % of the petroleum production is taken at sea and area of deployment and it cost scale are worrisome. It is associated, oily water production on a large scale, carrier 95% of the potential pollutant of activity whose final destination is the environment medium, terrestrial or maritime. Although diversified set of techniques and water treatment systems are in use or research, we propose an innovative system that operates in a sustainable way without chemical additives, for the good of the ecosystem. Labyrinth adsor-bent is used in metal spirals, and laboratory scale flow. Equipment and process patents are claimed. Treatments were performed at different flow rates and bands often monitored with control systems, some built, other bought for this purpose. Measurements of the levels of oil and grease (OGC) of efluents treaty remained within the range of legal framework under test conditions. Adsorbents were weighed before and after treatment for obtaining oil impregna-tion, the performance goal of vibratory action and treatment as a whole. Treatment technolo-gies in course are referenced, to compare performance, qualitatively and quantitatively. The vibration energy consumption is faced with and without conventional flotation and self-flotation. There are good prospects for the proposed, especially in reducing the residence time, by capillary action system. The impregnation dimensionless parameter was created and confronted with consecrated dimensionless parameters, on the vibrational version, such as Weber number and Froude number in quadratic form, referred to as vibrational criticality. Re-sults suggest limits to the vibration intensity

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This work develops a robustness analysis with respect to the modeling errors, being applied to the strategies of indirect control using Artificial Neural Networks - ANN s, belong to the multilayer feedforward perceptron class with on-line training based on gradient method (backpropagation). The presented schemes are called Indirect Hybrid Control and Indirect Neural Control. They are presented two Robustness Theorems, being one for each proposed indirect control scheme, which allow the computation of the maximum steady-state control error that will occur due to the modeling error what is caused by the neural identifier, either for the closed loop configuration having a conventional controller - Indirect Hybrid Control, or for the closed loop configuration having a neural controller - Indirect Neural Control. Considering that the robustness analysis is restrict only to the steady-state plant behavior, this work also includes a stability analysis transcription that is suitable for multilayer perceptron class of ANN s trained with backpropagation algorithm, to assure the convergence and stability of the used neural systems. By other side, the boundness of the initial transient behavior is assured by the assumption that the plant is BIBO (Bounded Input, Bounded Output) stable. The Robustness Theorems were tested on the proposed indirect control strategies, while applied to regulation control of simulated examples using nonlinear plants, and its results are presented

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In this work a modification on ANFIS (Adaptive Network Based Fuzzy Inference System) structure is proposed to find a systematic method for nonlinear plants, with large operational range, identification and control, using linear local systems: models and controllers. This method is based on multiple model approach. This way, linear local models are obtained and then those models are combined by the proposed neurofuzzy structure. A metric that allows a satisfactory combination of those models is obtained after the structure training. It results on plant s global identification. A controller is projected for each local model. The global control is obtained by mixing local controllers signals. This is done by the modified ANFIS. The modification on ANFIS architecture allows the two neurofuzzy structures knowledge sharing. So the same metric obtained to combine models can be used to combine controllers. Two cases study are used to validate the new ANFIS structure. The knowledge sharing is evaluated in the second case study. It shows that just one modified ANFIS structure is necessary to combine linear models to identify, a nonlinear plant, and combine linear controllers to control this plant. The proposed method allows the usage of any identification and control techniques for local models and local controllers obtaining. It also reduces the complexity of ANFIS usage for identification and control. This work has prioritized simpler techniques for the identification and control systems to simplify the use of the method

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In this work is proposed an indirect approach to the DualMode Adaptive Robust Controller (DMARC), combining the typicals transient and robustness properties of Variable Structure Systems, more specifically of Variable Structure Model Reference Adaptive Controller (VS-MRAC), with a smooth control signal in steady-state, typical of conventional Adaptive Controllers, as Model Reference Adaptive Controller (MRAC). The goal is to provide a more intuitive controller design, based on physical plant parameters, as resistances, inertia moments, capacitances, etc. Furthermore, with the objective to follow the evolutionary line of direct controllers, it will be proposed an indirect version for the Binary Model Reference Adaptive Controller (B-MRAC), that was the first controller attemptting to act as MRAC as well as VS-MRAC, depending on a pre-defined fixed parameter

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This work shows a study about the Generalized Predictive Controllers with Restrictions and their implementation in physical plants. Three types of restrictions will be discussed: restrictions in the variation rate of the signal control, restrictions in the amplitude of the signal control and restrictions in the amplitude of the Out signal (plant response). At the predictive control, the control law is obtained by the minimization of an objective function. To consider the restrictions, this minimization of the objective function is done by the use of a method to solve optimizing problems with restrictions. The chosen method was the Rosen Algorithm (based on the Gradient-projection). The physical plants in this study are two didactical systems of water level control. The first order one (a simple tank) and another of second order, which is formed by two tanks connected in cascade. The codes are implemented in C++ language and the communication with the system to be done through using a data acquisition panel offered by the system producer

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This paper describes the study, computer simulation and feasibility of implementation of vector control speed of an induction motor using for this purpose the Extended Kalman Filter as an estimator of rotor flux. The motivation for such work is the use of a control system that requires no sensors on the machine shaft, thus providing a considerable cost reduction of drives and their maintenance, increased reliability, robustness and noise immunity as compared to control systems with conventional sensors

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The control of industrial processes has become increasingly complex due to variety of factory devices, quality requirement and market competition. Such complexity requires a large amount of data to be treated by the three levels of process control: field devices, control systems and management softwares. To use data effectively in each one of these levels is extremely important to industry. Many of today s industrial computer systems consist of distributed software systems written in a wide variety of programming languages and developed for specific platforms, so, even more companies apply a significant investment to maintain or even re-write their systems for different platforms. Furthermore, it is rare that a software system works in complete isolation. In industrial automation is common that, software had to interact with other systems on different machines and even written in different languages. Thus, interoperability is not just a long-term challenge, but also a current context requirement of industrial software production. This work aims to propose a middleware solution for communication over web service and presents an user case applying the solution developed to an integrated system for industrial data capture , allowing such data to be available simplified and platformindependent across the network

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The pumping through progressing cavities system has been more and more employed in the petroleum industry. This occurs because of its capacity of elevation of highly viscous oils or fluids with great concentration of sand or other solid particles. A Progressing Cavity Pump (PCP) consists, basically, of a rotor - a metallic device similar to an eccentric screw, and a stator - a steel tube internally covered by a double helix, which may be rigid or deformable/elastomeric. In general, it is submitted to a combination of well pressure with the pressure generated by the pumping process itself. In elastomeric PCPs, this combined effort compresses the stator and generates, or enlarges, the clearance existing between the rotor and the stator, thus reducing the closing effect between their cavities. Such opening of the sealing region produces what is known as fluid slip or slippage, reducing the efficiency of the PCP pumping system. Therefore, this research aims to develop a transient three-dimensional computational model that, based on single-lobe PCP kinematics, is able to simulate the fluid-structure interaction that occurs in the interior of metallic and elastomeric PCPs. The main goal is to evaluate the dynamic characteristics of PCP s efficiency based on detailed and instantaneous information of velocity, pressure and deformation fields in their interior. To reach these goals (development and use of the model), it was also necessary the development of a methodology for generation of dynamic, mobile and deformable, computational meshes representing fluid and structural regions of a PCP. This additional intermediary step has been characterized as the biggest challenge for the elaboration and running of the computational model due to the complex kinematic and critical geometry of this type of pump (different helix angles between rotor and stator as well as large length scale aspect ratios). The processes of dynamic generation of meshes and of simultaneous evaluation of the deformations suffered by the elastomer are fulfilled through subroutines written in Fortan 90 language that dynamically interact with the CFX/ANSYS fluid dynamic software. Since a structural elastic linear model is employed to evaluate elastomer deformations, it is not necessary to use any CAE package for structural analysis. However, an initial proposal for dynamic simulation using hyperelastic models through ANSYS software is also presented in this research. Validation of the results produced with the present methodology (mesh generation, flow simulation in metallic PCPs and simulation of fluid-structure interaction in elastomeric PCPs) is obtained through comparison with experimental results reported by the literature. It is expected that the development and application of such a computational model may provide better details of the dynamics of the flow within metallic and elastomeric PCPs, so that better control systems may be implemented in the artificial elevation area by PCP

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The use of increasingly complex software applications is demanding greater investment in the development of such systems to ensure applications with better quality. Therefore, new techniques are being used in Software Engineering, thus making the development process more effective. Among these new approaches, we highlight Formal Methods, which use formal languages that are strongly based on mathematics and have a well-defined semantics and syntax. One of these languages is Circus, which can be used to model concurrent systems. It was developed from the union of concepts from two other specification languages: Z, which specifies systems with complex data, and CSP, which is normally used to model concurrent systems. Circus has an associated refinement calculus, which can be used to develop software in a precise and stepwise fashion. Each step is justified by the application of a refinement law (possibly with the discharge of proof obligations). Sometimes, the same laws can be applied in the same manner in different developments or even in different parts of a single development. A strategy to optimize this calculus is to formalise these application as a refinement tactic, which can then be used as a single transformation rule. CRefine was developed to support the Circus refinement calculus. However, before the work presented here, it did not provide support for refinement tactics. The aim of this work is to provide tool support for refinement tactics. For that, we develop a new module in CRefine, which automates the process of defining and applying refinement tactics that are formalised in the tactic language ArcAngelC. Finally, we validate the extension by applying the new module in a case study, which used the refinement tactics in a refinement strategy for verification of SPARK Ada implementations of control systems. In this work, we apply our module in the first two phases of this strategy

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The chart of control of Hotelling T2 has been the main statistical device used in monitoring multivariate processes. Currently the technological development of control systems and automation enabled a high rate of collection of information of the production systems in very short time intervals, causing a dependency between the results of observations. This phenomenon known as auto correlation causes in the statistical control of the multivariate processes a high rate of false alarms, prejudicing in the chart performance. This entails the violation of the assumption of independence and normality of the distribution. In this thesis we considered not only the correlation between two variables, but also the dependence between observations of the same variable, that is, auto correlation. It was studied by simulation, the bi variate case and the effect of auto correlation on the performance of the T2 chart of Hotelling.