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

Desenvolvimento de um software de comunicação sem fio aplicado à instrumentação de unidade de elevação de petróleo tipo Plunger Lift

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

Uma ferramenta de manipulação de pacotes para análise de protocolos de redes industriais baseados em TCP/IP

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

Implementação e análise de desempenho dos protocolos de criptografia neural e Diffie-Hellman em sistemas RFID utilizando uma plataforma embarcada

RFID (Radio Frequency Identification) identifies object by using the radio frequency which is a non-contact automatic identification technique. This technology has shown its powerful practical value and potential in the field of manufacturing, retailing, logistics and hospital automation. Unfortunately, the key problem that impacts the application of RFID system is the security of the information. Recently, researchers have demonstrated solutions to security threats in RFID technology. Among these solutions are several key management protocols. This master dissertations presents a performance evaluation of Neural Cryptography and Diffie-Hellman protocols in RFID systems. For this, we measure the processing time inherent in these protocols. The tests was developed on FPGA (Field-Programmable Gate Array) platform with Nios IIr embedded processor. The research methodology is based on the aggregation of knowledge to development of new RFID systems through a comparative analysis between these two protocols. The main contributions of this work are: performance evaluation of protocols (Diffie-Hellman encryption and Neural) on embedded platform and a survey on RFID security threats. According to the results the Diffie-Hellman key agreement protocol is more suitable for RFID systems

Uma fonte chaveada de 50kW com correção de fator de potência para alimentação de uma tocha de plasma Indutiva utilizando técnicas de controle digital

This work deals with the development of an experimental study on a power supply of high frequency that provides the toch plasmica to be implemented in PLASPETRO project, which consists of two static converters developed by using Insulated Gate Bipolar Transistor (IGBT). The drivers used to control these keys are triggered by Digital Signal Processor (DSP) through optical fibers to reduce problems with electromagnetic interference (EMI). The first stage consists of a pre-regulator in the form of an AC to DC converter with three-phase boost power factor correction which is the main theme of this work, while the second is the source of high frequency itself. A series-resonant inverter consists of four (4) cell inverters operating in a frequency around 115 kHz each one in soft switching mode, alternating itself to supply the load (plasma torch) an alternating current with a frequency of 450 kHz. The first stage has the function of providing the series-resonant inverter a DC voltage, with the value controlled from the power supply provided by the electrical system of the utility, and correct the power factor of the system as a whole. This level of DC bus voltage at the output of the first stage will be used to control the power transferred by the inverter to the load, and it may vary from 550 VDC to a maximum of 800 VDC. To control the voltage level of DC bus driver used a proportional integral (PI) controller and to achieve the unity power factor it was used two other proportional integral currents controllers. Computational simulations were performed to assist in sizing and forecasting performance. All the control and communications needed to stage supervisory were implemented on a DSP

Sistema Híbrido de Inferência Baseado em Análise de Componentes Principais e Redes Neurais Artificiais Aplicado a Plantas de Processamento de Gás Natural

Nowadays, where the market competition requires products with better quality and a constant search for cost savings and a better use of raw materials, the research for more efficient control strategies becomes vital. In Natural Gas Processin Units (NGPUs), as in the most chemical processes, the quality control is accomplished through their products composition. However, the chemical composition analysis has a long measurement time, even when performed by instruments such as gas chromatographs. This fact hinders the development of control strategies to provide a better process yield. The natural gas processing is one of the most important activities in the petroleum industry. The main economic product of a NGPU is the liquefied petroleum gas (LPG). The LPG is ideally composed by propane and butane, however, in practice, its composition has some contaminants, such as ethane and pentane. In this work is proposed an inferential system using neural networks to estimate the ethane and pentane mole fractions in LPG and the propane mole fraction in residual gas. The goal is to provide the values of these estimated variables in every minute using a single multilayer neural network, making it possibly to apply inferential control techniques in order to monitor the LPG quality and to reduce the propane loss in the process. To develop this work a NGPU was simulated in HYSYS R software, composed by two distillation collumns: deethanizer and debutanizer. The inference is performed through the process variables of the PID controllers present in the instrumentation of these columns. To reduce the complexity of the inferential neural network is used the statistical technique of principal component analysis to decrease the number of network inputs, thus forming a hybrid inferential system. It is also proposed in this work a simple strategy to correct the inferential system in real-time, based on measurements of the chromatographs which may exist in process under study