94 resultados para Arduino (Controlador programável)

em Universidade Federal do Rio Grande do Norte(UFRN)


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The Wireless Sensor Networks (WSN) methods applied to the lifting of oil present as an area with growing demand technical and scientific in view of the optimizations that can be carried forward with existing processes. This dissertation has as main objective to present the development of embedded systems dedicated to a wireless sensor network based on IEEE 802.15.4, which applies the ZigBee protocol, between sensors, actuators and the PLC (Programmable Logic Controller), aiming to solve the present problems in the deployment and maintenance of the physical communication of current elevation oil units based on the method Plunger-Lift. Embedded systems developed for this application will be responsible for acquiring information from sensors and control actuators of the devices present at the well, and also, using the Modbus protocol to make this network becomes transparent to the PLC responsible for controlling the production and delivery information for supervisory SISAL

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The Electrical Submersible Pumping is an artificial lift method for oil wells employed in onshore and offshore areas. The economic revenue of the petroleum production in a well depends on the oil flow and the availability of lifting equipment. The fewer the failures, the lower the revenue shortfall and costs to repair it. The frequency with which failures occur depends on the operating conditions to which the pumps are submitted. In high-productivity offshore wells monitoring is done by operators with engineering support 24h/day, which is not economically viable for the land areas. In this context, the automation of onshore wells has clear economic advantages. This work proposes a system capable of automatically control the operation of electrical submersible pumps, installed in oil wells, by an adjustment at the electric motor rotation based on signals provided by sensors installed on the surface and subsurface, keeping the pump operating within the recommended range, closest to the well s potential. Techniques are developed to estimate unmeasured variables, enabling the automation of wells that do not have all the required sensors. The automatic adjustment, according to an algorithm that runs on a programmable logic controller maintains the flow and submergence within acceptable parameters avoiding undesirable operating conditions, as the gas interference and high engine temperature, without need to resort to stopping the engine, which would reduce the its useful life. The control strategy described, based on modeling of physical phenomena and operational experience reported in literature, is materialized in terms of a fuzzy controller based on rules, and all generated information can be accompanied by a supervisory system

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In this thesis, it is developed the robustness and stability analysis of a variable structure model reference adaptive controller considering the presence of disturbances and unmodeled dynamics. The controller is applied to uncertain, monovariable, linear time-invariant plants with relative degree one, and its development is based on the indirect adaptive control. In the direct approach, well known in the literature, the switching laws are designed for the controller parameters. In the indirect one, they are designed for the plant parameters and, thus, the selection of the relays upper bounds becomes more intuitive, whereas they are related to physical parameters, which present uncertainties that can be known easier, such as resistances, capacitances, inertia moments and friction coefficients. Two versions for the controller algorithm with the stability analysis are presented. The global asymptotic stability with respect to a compact set is guaranteed for both cases. Simulation results under adverse operation conditions in order to verify the theoretical results and to show the performance and robustness of the proposed controller are showed. Moreover, for practical purposes, some simplifications on the original algorithm are developed

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The so-called Dual Mode Adaptive Robust Control (DMARC) is proposed. The DMARC is a control strategy which interpolates the Model Reference Adaptive Control (MRAC) and the Variable Structure Model Reference Adaptive Control (VS-MRAC). The main idea is to incorporate the transient performance advantages of the VS-MRAC controller with the smoothness control signal in steady-state of the MRAC controller. Two basic algorithms are developed for the DMARC controller. In the first algorithm the controller's adjustment is made, in real time, through the variation of a parameter in the adaptation law. In the second algorithm the control law is generated, using fuzzy logic with Takagi-Sugeno s model, to obtain a combination of the MRAC and VS-MRAC control laws. In both cases, the combined control structure is shown to be robust to the parametric uncertainties and external disturbances, with a fast transient performance, practically without oscillations, and a smoothness steady-state control signal

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In this work, the variable structure adaptive pole placement controller (VS-APPC) robustness and performance are evaluated and this algorithm is applied in a motor control system. The controller robustness evaluation will be done through simulations, where will be introduced in the system the following adversities: time delay, actuator response boundeds, disturbances, parametric variation and unmodeled dynamics. The VS-APPC will be compared with PI control, pole placement control (PPC) and adaptive pole placement controller (APPC). The VS-APPC will be simulated to track a step and a sine reference. It will be applied in a three-phase induction motor control system to track a sine signal in the stator reference frame. Simulation and experimental results will prove the efficiency and robustness of this control strategy

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On this paper, it is made a comparative analysis among a controller fuzzy coupled to a PID neural adjusted by an AGwith several traditional control techniques, all of them applied in a system of tanks (I model of 2nd order non lineal). With the objective of making possible the techniques involved in the comparative analysis and to validate the control to be compared, simulations were accomplished of some control techniques (conventional PID adjusted by GA, Neural PID (PIDN) adjusted by GA, Fuzzy PI, two Fuzzy attached to a PID Neural adjusted by GA and Fuzzy MISO (3 inputs) attached to a PIDN adjusted by GA) to have some comparative effects with the considered controller. After doing, all the tests, some control structures were elected from all the tested techniques on the simulating stage (conventional PID adjusted by GA, Fuzzy PI, two Fuzzy attached to a PIDN adjusted by GA and Fuzzy MISO (3 inputs) attached to a PIDN adjusted by GA), to be implemented at the real system of tanks. These two kinds of operation, both the simulated and the real, were very important to achieve a solid basement in order to establish the comparisons and the possible validations show by the results

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The predictive control technique has gotten, on the last years, greater number of adepts in reason of the easiness of adjustment of its parameters, of the exceeding of its concepts for multi-input/multi-output (MIMO) systems, of nonlinear models of processes could be linearised around a operating point, so can clearly be used in the controller, and mainly, as being the only methodology that can take into consideration, during the project of the controller, the limitations of the control signals and output of the process. The time varying weighting generalized predictive control (TGPC), studied in this work, is one more an alternative to the several existing predictive controls, characterizing itself as an modification of the generalized predictive control (GPC), where it is used a reference model, calculated in accordance with parameters of project previously established by the designer, and the application of a new function criterion, that when minimized offers the best parameters to the controller. It is used technique of the genetic algorithms to minimize of the function criterion proposed and searches to demonstrate the robustness of the TGPC through the application of performance, stability and robustness criterions. To compare achieves results of the TGPC controller, the GCP and proportional, integral and derivative (PID) controllers are used, where whole the techniques applied to stable, unstable and of non-minimum phase plants. The simulated examples become fulfilled with the use of MATLAB tool. It is verified that, the alterations implemented in TGPC, allow the evidence of the efficiency of this algorithm

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During a petroleum well production process, It is common the slmultaneous oil and water production, in proportion that can vary from 0% up to values close to 100% of water. Moreover, the production flows can vary a lot, depending on the charaeteristies of eaeh reservoir. Thus being, the meters used in field for the flow and BSW (water in the oil) measurement must work well in wide bands of operation. For the evaluation of the operation of these meters, in the different operation conditions, a Laboratory will be built in UFRN, that has for objective to evaluate in an automatic way the processes of flow and BSW petroleum measurement, considering different operation conditions. The good acting of these meters is fundamental for the accuracy of the measures of the volumes of production liquid and rude of petroleum. For the measurement of this production, the petroleum companies use meters that should indicate the values with tha largast possible accuracy and to respect a series of conditions and minimum requirements, estabelished by the united Entrance ANP/INMETRO 19106/2000. The laboratory of Evafuation of the Processes of Measurement of Flow and BSW to be built will possess an oil tank basically, a tank of water, besides a mixer, a tank auditor, a tank for separation and a tank of residues for discard of fluids, fundamental for the evaluation of the flow metars and BSW. The whole process will be automated through the use of a Programmable Logicat Controller (CLP) and of a supervisory system.This laboratory besides allowing the evaluation of flow meters and BSW used by petroleum companies, it will make possible the development of researches related to the automation. Besides, it will be a collaborating element to the development of the Computer Engineering and Automation Department, that it will propitiate the evolution of the faculty and discente, qualifying them for a job market in continuous growth. The present work describes the project of automation of the laboratory that will be built at of UFRN. The system will be automated using a Programmable Logical Controller and a supervisory system. The programming of PLC and the screens of the supervisory system were developed in this work

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This dissertation aims to develop a software applied to a communication system for a wireless sensor network (WSN) for tracking analog and digital variables and control valve of the gas flow in artificial oil s elevation units, Plunger Lift type. The reason for this implementation is due to the fact that, in the studied plant configuration, the sensors communicate with the PLC (Programmable and Logic Controller) by the cables and pipelines, making any changes in that system, such as changing the layout of it, as well as inconveniences that arise from the nature of the site, such as the vicinity s animals presence that tend to destroy the cables for interconnection of sensors to the PLC. For software development, was used communication polling method via SMAC protocol (Simple Medium Access ControlIEEE 802.15.4 standard) in the CodeWarrior environment to which generated a firmware, loaded into the WSN s transceivers, present in the kit MC13193-EVK, (all items described above are owners of Freescale Semiconductors Inc.). The network monitoring and parameterization used in its application, was developed in LabVIEW software from National Instruments. The results were obtained through the observation of the network s behavior of sensors proposal, focusing on aspects such as: indoor and outdoor quantity of packages received and lost, general aspects of reliability in data transmission, coexistence with other types of wireless networks and power consumption under different operating conditions. The results were considered satisfactory, which showed the software efficiency in this communication system

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This work presents a packet manipulation tool developed to realize tests in industrial devices that implements TCP/IP-based communication protocols. The tool was developed in Python programming language, as a Scapy extension. This tool, named IndPM- Industrial Packet Manipulator, can realize vulnerability tests in devices of industrial networks, industrial protocol compliance tests, receive server replies and utilize the Python interpreter to build tests. The Modbus/TCP protocol was implemented as proof-of-concept. The DNP3 over TCP protocol was also implemented but tests could not be realized because of the lack of resources. The IndPM results with Modbus/TCP protocol show some implementation faults in a Programmable Logic Controller communication module frequently utilized in automation companies

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Postsurgical complication of hypertension may occur in cardiac patients. To decrease the chances of complication it is necessary to reduce elevated blood pressure as soon as possible. Continuous infusion of vasodilator drugs, such as sodium nitroprusside (Nipride), would quickly lower the blood pressure in most patients. However, each patient has a different sensitivity to infusion of Nipride. The parameters and the time delays of the system are initially unknown. Moreover, the parameters of the transfer function associated with a particular patient are time varying. the objective of the study is to develop a procedure for blood pressure control i the presence of uncertainty of parameters and considerable time delays. So, a methodology was developed multi-model, and for each such model a Preditive Controller can be a priori designed. An adaptive mechanism is then needed for deciding which controller should be dominant for a given plant

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This work deals with an on-line control strategy based on Robust Model Predictive Control (RMPC) technique applied in a real coupled tanks system. This process consists of two coupled tanks and a pump to feed the liquid to the system. The control objective (regulator problem) is to keep the tanks levels in the considered operation point even in the presence of disturbance. The RMPC is a technique that allows explicit incorporation of the plant uncertainty in the problem formulation. The goal is to design, at each time step, a state-feedback control law that minimizes a 'worst-case' infinite horizon objective function, subject to constraint in the control. The existence of a feedback control law satisfying the input constraints is reduced to a convex optimization over linear matrix inequalities (LMIs) problem. It is shown in this work that for the plant uncertainty described by the polytope, the feasible receding horizon state feedback control design is robustly stabilizing. The software implementation of the RMPC is made using Scilab, and its communication with Coupled Tanks Systems is done through the OLE for Process Control (OPC) industrial protocol

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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 work presents an analysis of the control law based on an indirect hybrid scheme using neural network, initially proposed for O. Adetona, S. Sathanathan and L. H. Keel. Implementations of this control law, for a level plant of second order, was resulted an oscillatory behavior, even if the neural identifier has converged. Such results had motivated the investigation of the applicability of that law. Starting from that, had been made stability mathematical analysis and several implementations, with simulated plants and with real plants, for analyze the problem. The analysis has been showed the law was designed being despised some components of dynamic of the plant to be controlled. Thus, for plants that these components have a significant influence in its dynamic, the law tends to fail