Determinantes locais da decomposição foliar e de raízes finais em um ecossistema semiárido do nordeste brasileiro

The decomposition process exercises an extensive control over the carbon cycle, affecting its availability and nutrient cycling in terrestrial ecosystems. The understanding of leaf decomposition patterns above the soil and fine roots decomposition below the soil is necessary and essential to identify and quantify more accurately the flow of energy and matter in forest systems. There is still a lack of studies and a large gap in the knowledge about what environmental variables act as local determinants over decomposition drivers. The knowledge about the decomposition process is still immature for Brazilian semiarid region. The aim of this study was to analyze the decomposition process (on leaves and fine roots) of a mixture of three native species for 12 months in a semiarid ecosystem in Northeast Brazil. We also examined whether the rate of decomposition can be explained by local environmental factors, specifically plant species richness, plant density and biomass, soil macro-arthropods species richness and abundance, amount of litterfall and fine root stock. Thirty sampling points were randomly distributed within an area of 2000 m x 500 m. To determine the decomposition rate, the litterbag technique was used and the data analysis were made with multiple regressions. There was a high degradation of dead organic matter along the experiment. Above ground plant biomass was the only environmental local factor significantly related to leaf decomposition. The density of vegetation and litter production were positively and negatively related to decay rates of fine roots, respectively. The results suggest that Caatinga spatial heterogeneity may exert strong influences over the decomposition process, taking into account the action of environmental factors related to organic matter exposure of and the consequent action of solar radiation as the decomposition process main controller in this region

Educação corporativa para Micro e Pequenas empresas: aplicação do MADEC em empresas do setor supermercadista

This study searches to supply an existing gap in the empirical research about the performance of controllers of Micron and Small Companies (MSCs) in the context of corporative education (EC) through the Method of Support of Decision in Corporative Education (MSDCE). In the context of MCSs, this is a pioneering work, for other works related to this thematic searched in literature are limited to conjecture the possibility of its implantation via cooperation between companies; moreover, they do not apply any type of diagnosis method or viability. The object of study is an association of supermarkets of the city of Natal/RN, composed by 16 stores, of what 14 had been searched. The main objective of this work was to apply the first stage of the MSDCE and to verify the possibility of implanting the Corporative Education in the searched MSCs. As a result, it was obtained the profile of the companies and the validation of the above-mentioned Method. The phase of diagnosis conceived through the implantation of the first stage occurred through visits to the stores, interviews, application of questionnaires and place observation. The first stage - strategical analysis for professional education - was divided in two phases: analysis of the current corporative situation and available identification of the involved difficulties and resources. The implantation of the first stage of the MSDCE in the Association of Supermarkets Parceiros da Economia demanded a mapping of abilities and demonstrated how the education management works, the main difficulties and limitations of the MCSs of the supermerket branch of Natal/RN. Beyond the technological aspects, it was verified that cultural and educational aspects need to be worked to reach efficiency in the process of implantation of a corporative education program

Impactos da legislação ambiental brasileira na exportação de camarão: um estudo com exportadores de camarão do Rio Grande do Norte

Brazilian exportations come growing in a constant form in the last years, stimulated for the globalization and public politics directed toward the increase of the internal surplus. In this context the objective of this work was to investigate the perception of the shrimp exporting entrepreneurs of Rio Grande do Norte, with relation to the impact of the Brazilian environmental legislation in the companies competitiveness at the external market. From data collected from the controllers of the companies, it was used a survey methodology, with exploratory and descriptive character. The results found in this study indicate that the companies, in general way, understand that the environmental legal requirements do not confuse nor help in the search and conquest of new international markets. A little more of the half of the researched companies, does not see the legislation rigid as important factor of competitiveness. However a sufficiently significant percentage, already has a more strategical vision on the subject, or at least already it heard to speak on such possibility

Controle vetorial de velocidade de uma máquina de indução sem mancais trifásica com bobinado dividido utilizando estimação neural de fluxo

This work describes the study and the implementation of the vector speed control for a three-phase Bearingless induction machine with divided winding of 4 poles and 1,1 kW using the neural rotor flux estimation. The vector speed control operates together with the radial positioning controllers and with the winding currents controllers of the stator phases. For the radial positioning, the forces controlled by the internal machine magnetic fields are used. For the radial forces optimization , a special rotor winding with independent circuits which allows a low rotational torque influence was used. The neural flux estimation applied to the vector speed controls has the objective of compensating the parameter dependences of the conventional estimators in relation to the parameter machine s variations due to the temperature increases or due to the rotor magnetic saturation. The implemented control system allows a direct comparison between the respective responses of the speed and radial positioning controllers to the machine oriented by the neural rotor flux estimator in relation to the conventional flux estimator. All the system control is executed by a program developed in the ANSI C language. The DSP resources used by the system are: the Analog/Digital channels converters, the PWM outputs and the parallel and RS-232 serial interfaces, which are responsible, respectively, by the DSP programming and the data capture through the supervisory system

Análise e desenvolvimento de controladores preditivos multivariáveis baseados em multi-modelos bilineares

This work addresses issues related to analysis and development of multivariable predictive controllers based on bilinear multi-models. Linear Generalized Predictive Control (GPC) monovariable and multivariable is shown, and highlighted its properties, key features and applications in industry. Bilinear GPC, the basis for the development of this thesis, is presented by the time-step quasilinearization approach. Some results are presented using this controller in order to show its best performance when compared to linear GPC, since the bilinear models represent better the dynamics of certain processes. Time-step quasilinearization, due to the fact that it is an approximation, causes a prediction error, which limits the performance of this controller when prediction horizon increases. Due to its prediction error, Bilinear GPC with iterative compensation is shown in order to minimize this error, seeking a better performance than the classic Bilinear GPC. Results of iterative compensation algorithm are shown. The use of multi-model is discussed in this thesis, in order to correct the deficiency of controllers based on single model, when they are applied in cases with large operation ranges. Methods of measuring the distance between models, also called metrics, are the main contribution of this thesis. Several application results in simulated distillation columns, which are close enough to actual behaviour of them, are made, and the results have shown satisfactory

Controle preditivo não linear baseado no modelo de Hammerstein com prova de estabilidade

The Predictive Controller has been receiving plenty attention in the last decades, because the need to understand, to analyze, to predict and to control real systems has been quickly growing with the technological and industrial progress. The objective of this thesis is to present a contribution for the development and implementation of Nonlinear Predictive Controllers based on Hammerstein model, as well as to its make properties evaluation. In this case, in the Nonlinear Predictive Controller development the time-step linearization method is used and a compensation term is introduced in order to improve the controller performance. The main motivation of this thesis is the study and stability guarantee for the Nonlinear Predictive Controller based on Hammerstein model. In this case, was used the concepts of sections and Popov Theorem. Simulation results with literature models shows that the proposed approaches are able to control with good performance and to guarantee the systems stability

Controle adaptativo robusto para um modelo desacoplado de um robô móvel

This thesis presents a new structure of robust adaptive controller applied to mobile robots (surface mobile robot) with nonholonomic constraints. It acts in the dynamics and kinematics of the robot, and it is split in two distinct parts. The first part controls the robot dynamics, using variable structure model reference adaptive controllers. The second part controls the robot kinematics, using a position controller, whose objective is to make the robot to reach any point in the cartesian plan. The kinematic controller is based only on information about the robot configuration. A decoupling method is adopted to transform the linear model of the mobile robot, a multiple-input multiple-output system, into two decoupled single-input single-output systems, thus reducing the complexity of designing the controller for the mobile robot. After that, a variable structure model reference adaptive controller is applied to each one of the resulting systems. One of such controllers will be responsible for the robot position and the other for the leading angle, using reference signals generated by the position controller. To validate the proposed structure, some simulated and experimental results using differential drive mobile robots of a robot soccer kit are presented. The simulator uses the main characteristics of real physical system as noise and non-linearities such as deadzone and saturation. The experimental results were obtained through an C++ program applied to the robot soccer kit of Microrobot team at the LACI/UFRN. The simulated and experimental results are presented and discussed at the end of the text

Técnicas de inteligência artificial para a geração dinâmica de set points para uma coluna de destilação

Artificial Intelligence techniques are applied to improve performance of a simulated oil distillation system. The chosen system was a debutanizer column. At this process, the feed, which comes to the column, is segmented by heating. The lightest components become steams, by forming the LPG (Liquefied Petroleum Gas). The others components, C5+, continue liquid. In the composition of the LPG, ideally, we have only propane and butanes, but, in practice, there are contaminants, for example, pentanes. The objective of this work is to control pentane amount in LPG, by means of intelligent set points (SP s) determination for PID controllers that are present in original instrumentation (regulatory control) of the column. A fuzzy system will be responsible for adjusting the SP's, driven by the comparison between the molar fraction of the pentane present in the output of the plant (LPG) and the desired amount. However, the molar fraction of pentane is difficult to measure on-line, due to constraints such as: long intervals of measurement, high reliability and low cost. Therefore, an inference system was used, based on a multilayer neural network, to infer the pentane molar fraction through secondary variables of the column. Finally, the results shown that the proposed control system were able to control the value of pentane molar fraction under different operational situations

Um sistema para estimação da vazão de gás de poços produzindo por Plunger Lift para vaso separador de teste em plataformas de petróleo

This work intends to analyze the behavior of the gas flow of plunger lift wells producing to well testing separators in offshore production platforms to aim a technical procedure to estimate the gas flow during the slug production period. The motivation for this work appeared from the expectation of some wells equipped with plunger lift method by PETROBRAS in Ubarana sea field located at Rio Grande do Norte State coast where the produced fluids measurement is made in well testing separators at the platform. The oil artificial lift method called plunger lift is used when the available energy of the reservoir is not high enough to overcome all the necessary load losses to lift the oil from the bottom of the well to the surface continuously. This method consists, basically, in one free piston acting as a mechanical interface between the formation gas and the produced liquids, greatly increasing the well s lifting efficiency. A pneumatic control valve is mounted at the flow line to control the cycles. When this valve opens, the plunger starts to move from the bottom to the surface of the well lifting all the oil and gas that are above it until to reach the well test separator where the fluids are measured. The well test separator is used to measure all the volumes produced by the well during a certain period of time called production test. In most cases, the separators are designed to measure stabilized flow, in other words, reasonably constant flow by the use of level and pressure electronic controllers (PLC) and by assumption of a steady pressure inside the separator. With plunger lift wells the liquid and gas flow at the surface are cyclical and unstable what causes the appearance of slugs inside the separator, mainly in the gas phase, because introduce significant errors in the measurement system (e.g.: overrange error). The flow gas analysis proposed in this work is based on two mathematical models used together: i) a plunger lift well model proposed by Baruzzi [1] with later modifications made by Bolonhini [2] to built a plunger lift simulator; ii) a two-phase separator model (gas + liquid) based from a three-phase separator model (gas + oil + water) proposed by Nunes [3]. Based on the models above and with field data collected from the well test separator of PUB-02 platform (Ubarana sea field) it was possible to demonstrate that the output gas flow of the separator can be estimate, with a reasonable precision, from the control signal of the Pressure Control Valve (PCV). Several models of the System Identification Toolbox from MATLAB® were analyzed to evaluate which one better fit to the data collected from the field. For validation of the models, it was used the AIC criterion, as well as a variant of the cross validation criterion. The ARX model performance was the best one to fit to the data and, this way, we decided to evaluate a recursive algorithm (RARX) also with real time data. The results were quite promising that indicating the viability to estimate the output gas flow rate from a plunger lift well producing to a well test separator, with the built-in information of the control signal to the PCV

Controle Adaptativo Robusto para Filtros Ativos de Potência Paralelo

Conventional control strategies used in shunt active power filters (SAPF) employs real-time instantaneous harmonic detection schemes which is usually implements with digital filters. This increase the number of current sensors on the filter structure which results in high costs. Furthermore, these detection schemes introduce time delays which can deteriorate the harmonic compensation performance. Differently from the conventional control schemes, this paper proposes a non-standard control strategy which indirectly regulates the phase currents of the power mains. The reference currents of system are generated by the dc-link voltage controller and is based on the active power balance of SAPF system. The reference currents are aligned to the phase angle of the power mains voltage vector which is obtained by using a dq phase locked loop (PLL) system. The current control strategy is implemented by an adaptive pole placement control strategy integrated to a variable structure control scheme (VS-APPC). In the VS-APPC, the internal model principle (IMP) of reference currents is used for achieving the zero steady state tracking error of the power system currents. This forces the phase current of the system mains to be sinusoidal with low harmonics content. Moreover, the current controllers are implemented on the stationary reference frame to avoid transformations to the mains voltage vector reference coordinates. This proposed current control strategy enhance the performance of SAPF with fast transient response and robustness to parametric uncertainties. Experimental results are showing for determining the effectiveness of SAPF proposed control system

Determinação dos parâmetros do controlador preditivo generalizado com função de pesos variante no tempo através de algoritmos genéticos

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

Estrutura ANFIS modificada para identificação e controle de plantas com ampla faixa de operação e não linearidade acentuada

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

Sistemas de automação e supervisão do laboratório de avaliação dos processos de medição de vazão e BSW

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

Desenvolvimento e avaliação de controladores preditivos baseados em modelos biliares

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Controle preditivo bilinear aplicado a um motor de indução

The present work is based on the applied bilinear predictive control applied to an induction motor. As in particular case of the technique based on predictive control in nonlinem systems, these have desperted great interest, a time that present the advantage of being simpler than the non linear in general and most representative one than the linear one. One of the methods, adopted here, uses the linear model "quasi linear for step of time" based in Generalized Predictive Control. The modeling of the induction motor is made by the Vectorial control with orientation given for the indirect rotor. The system is formed by an induction motor of 3 cv with rotor in squirregate, set in motion for a group of benches of tests developed for this work, presented resulted for a variation of +5% in the value of set-point and for a variation of +10% and -10% in the value of the applied nominal load to the motor. The results prove a good efficiency of the predictive bilinear controllers, then compared with the linear cases