Estabilidade e robustez de um controlador adaptativo indireto por um modelo de referência e estrutura variável

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

Controlador em modo dual adaptativo robusto - DMARC

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

Avaliação de robustez, desempenho e aplicação do controlador adaptativo por posicionamento de pólos e estrutura variável

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

Análise comparativa do desempenho de um Controlador Fuzzy acoplado a um PID Neural sintonizado por um Algoritmo Genético com Controladores Inteligentes Convencionais

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

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

Controlador preditivo generalizado multi-modelo aplicado ao controle de pressão arterial

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

Uma abordagem indireta para o Controlador em Modo Dual Adaptativo Robusto

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

Estudo e implementação em plantas físicas de um controlador preditivo generalizado com restrições

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

Análise de um controlador baseado no Jacobiano estimado da planta através de uma rede neural

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

Uma proposta de um controlador adaptativo por posicionamento de pólos e estrutura variável

There are two main approaches for using in adaptive controllers. One is the so-called model reference adaptive control (MRAC), and the other is the so-called adaptive pole placement control (APPC). In MRAC, a reference model is chosen to generate the desired trajectory that the plant output has to follow, and it can require cancellation of the plant zeros. Due to its flexibility in choosing the controller design methodology (state feedback, compensator design, linear quadratic, etc.) and the adaptive law (least squares, gradient, etc.), the APPC is the most general type of adaptive control. Traditionally, it has been developed in an indirect approach and, as an advantage, it may be applied to non-minimum phase plants, because do not involve plant zero-pole cancellations. The integration to variable structure systems allows to aggregate fast transient and robustness to parametric uncertainties and disturbances, as well. In this work, a variable structure adaptive pole placement control (VS-APPC) is proposed. Therefore, new switching laws are proposed, instead of using the traditional integral adaptive laws. Additionally, simulation results for an unstable first order system and simulation and practical results for a three-phase induction motor are shown

Estudo e implementação de um controlador preditivo generalizado bilinear compensado adaptativo

The present work presents the study and implementation of an adaptive bilinear compensated generalized predictive controller. This work uses conventional techniques of predictive control and includes techniques of adaptive control for better results. In order to solve control problems frequently found in the chemical industry, bilinear models are considered to represent the dynamics of the studied systems. Bilinear models are simpler than general nonlinear model, however it can to represent the intrinsic not-linearities of industrial processes. The linearization of the model, by the approach to time step quasilinear , is used to allow the application of the equations of the generalized predictive controller (GPC). Such linearization, however, generates an error of prediction, which is minimized through a compensation term. The term in study is implemented in an adaptive form, due to the nonlinear relationship between the input signal and the prediction error.Simulation results show the efficiency of adaptive predictive bilinear controller in comparison with the conventional.

Controlador adaptativo por posicionamento de pólos e estrutura variável aplicado ao controle de geradores eólicos baseados em máquina de indução duplamente alimentada

In the last decade, the renewable energy sources have present a major propulsion in the world due to several factors: political, environmental, financial and others. Within this context, we have in particular the energy obtained through wind, wind energy - that has highlighted with rapid growth in recent years, including in Brazil, mostly in the Northeast, due to it s benefit-cost between the clean energies. In this context, we propose to compare the variable structure adaptive pole placement control (VS-APPC) with a traditional control technique proportional integral controller (PI), applied to set the control of machine side in a conversion system using a wind generator based on Double-Fed Induction Generator (DFIG). Robustness and performance tests were carried out to the uncertainties of the internal parameters of the machine and variations of speed reference.

Controlador preditivo não linear aplicado ao controle de golfadas em processos de produção de petróleo

Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

Projeto em FPGA de um controlador unificado para correção de fator de potência em retificadores boost bidirecionais monofásicos

The use of Field Programmable Gate Array (FPGA) for development of digital control strategies for power electronics applications has aroused a growing interest of many researchers. This interest is due to the great advantages offered by FPGA, which include: lower design effort, high performance and highly flexible prototyping. This work proposes the development and implementation of an unified one-cycle controller for boost CFP rectifier based on FPGA. This controller can be applied to a total of twelve converters, six inverters and six rectifiers defined by four single phase VSI topologies and three voltage modulation types. The topologies considered in this work are: full-bridge, interleaved full-bridge, half-bridge and interleaved half-bridge. While modulations are classified in bipolar voltage modulation (BVM), unipolar voltage modulation (UVM) and clamped voltage modulation (CVM). The proposed project is developed and prototyped using tools Matlab/Simulink® together with the DSP Builder library provided by Altera®. The proposed controller was validated with simulation and experimental results

Controlador adaptativo backstepping a estrutura variável

Neste trabalho, um controlador adaptativo backstepping a estrutura variável (Variable Structure Adaptive Backstepping Controller, VS-ABC) é apresentado para plantas monovariáveis, lineares e invariantes no tempo com grau relativo unitário. Ao invés das tradicionais leis integrais para estimação dos parâmetros da planta, leis chaveadas são utilizadas com o objetivo de aumentar a robustez em relação a incertezas paramétricas e distúrbios externos, bem como melhorar o desempenho transitório do sistema. Adicionalmente, o projeto do novo controlador é mais intuitivo quando comparado ao controlador backstepping original, uma vez que os relés introduzidos apresentam amplitudes diretamente relacionadas com os parâmetros nominais da planta. Esta nova abordagem, com uso de estrutura variável, também reduz a complexidade das implementações práticas, motivando a utilização de componentes industriais, tais como, FPGAs (Field Programmable Gate Arrays ), MCUs (Microcontrollers) e DSPs (Digital Signal Processors). Simulações preliminares para um sistema instável de primeira e segunda ordem são apresentadas de modo a corroborar os estudos. Um dos exemplos de Rohrs é ainda abordado através de simulações, para os dois cenários adaptativos: o controlador backstepping adaptativo original e o VS-ABC