Walter Barra

Identification, digital control and fuzzy logic techniques applied to a synchronous generator

The experimental results obtained in the design and implementation of an decoupled digital speed and voltage controller for a micro-energy system are reported in this work. The studied system is formed by a 9 Kw DC motor driving a 10 KVA synchronous machine. There are two control loops in the proposed controller: the speed control (speed governor) and the control of the stators voltage (automatic voltage regulator). Each control loop was designed using linear control techniques and fuzzy control techniques. Tests on the system show the performance of the proposed controllers.

New Fuzzy Control Strategies Applied to the DFIG Converter in Wind Generation Systems

This paper presents new fuzzy control strategies which may be applied to the converter connected to the rotor of doubly fed induction generators (DFIG) composing a variable speed wind generation system connected to a real electrical grid. The fuzzy control proposed strategies are of the type supervised “look-up-table”. The performance of these intelligent controllers are compare with the fixed parameters PI controllers for fault ocurrence in the power system. The fuzzy controllers are supposed to better the transient performance of the electrical power system as compared with the conventional PI controllers. The obtained results from simulation studies have of the fuzzy controllers. To formulate the simulation studies an equivalent mathematical model of a significant number of wind turbines was implemented using the MATLABTM software packcage.

Self-tunning Control Methodologies Applied to the Automatic Voltage Control of a Synchronous Generator

In this paper, the experimental results obtained in the design and implementation of a self-tunning voltage controller for a micro energy system are analyzed. Two types of indirect adaptive self-tuning schemes are proposed. Both uses a recursive estimation scheme based on the well known Least Squares method. The difference between them is the controller formulation methodology: one uses the pole placement method and the other uses the generalized predictive control. Tests shows the comparison performance of the proposed adaptive controllers versus fixed digital controllers.

Digital PI fuzzy control strategies applied to an electric microgenerator system

This paper investigates digital modeling and control strategies applied to the voltage regulation of a microgenerator system, placed in the Electric Energy Generation Laboratory of Federal University of Para. Identification parametric techniques are used in order to obtain a representative model for the controller design. With a suitable model, controllers of proportional integral type are designed, based on the root locus and fuzzy systems strategies, in order to improve the voltage regulation of the microgenerator system.

Técnica de controle preditivo baseado em modelo aplicada ao controle de tensão de um gerador síncrono - resultados experimentais

Neste trabalho serao apresentados os resultados da avaliacao experimental de uma metodologia de controle digital preditivo auto-ajustavel aplicada ao controle de tensao de um sistema de geracao de energia de escala reduzida. Um estimador recursivo baseado no conhecido metodo de minimos quadrados e utilizado na etapa de identificacao do controlador preditivo proposto. A etapa de calculo da lei de controle e realizada com o algoritmo Generalized Predictive Controller (GPC). A avaliacao experimental foi realizada com testes de resposta ao degrau e rastreamento aplicados em diferentes condicoes operacionais do sistema de potencia estudado. Para fins de comparacao, tambem serao apresentados os resultados da avaliacao de um controlador auto-ajustavel que utiliza o metodo de alocacao de polos para a sintese do sinal de controle e tres controladores digitais com parâmetros fixos.

Creational Object-Oriented Design Pattern Applied to the Development of Software Tools for Electric Power Systems Dynamic Simulations

The development of software for dynamic simulation of electrical power systems requires a comprehensive range of complex studies, which encompasses many areas of electrical engineering as well as software engineering. This study aims at to develop an efficient strategy applied to the development of software tools for dynamic power systems simulations studies. The proposed strategy is based on the object-oriented creational pattern. This approach has the advantage of makes easy the application development process, by performing a mapping between block diagram model representation and the corresponding specialized classes. Firstly, a conceptual mapping between block diagram and the object-oriented paradigm, based on the Factory Method, is carried out. After that, some flexible strategies are presented in order to obtain an improved efficiency for the numerical routines, based on the Builder standard. This allows for the parameterization of the selected numerical integration techniques. The proposed strategy was evaluated by using a 4-generator multi-machine power system. The simulation results shown that the proposed strategy was able to provides a good power system dynamic performance.

Estabilizador neural não-linear para sistemas de potência treinado por rede de controladores lineares

A utilizacao de Estabilizadores de Sistemas de Potencia (ESP), para amortecer oscilacoes eletromecânicas de pequena magnitude e baixa frequencia, e cada vez mais importante na operacao dos modernos sistemas eletricos. Estabilizadores convencionais, com estrutura e parâmetros fixos, tem sido utilizados com essa finalidade ha algumas decadas, porem existem regioes de operacao do sistema nas quais esses estabilizadores lineares nao sao tao eficientes, especialmente quando comparados com estabilizadores projetados atraves de modernas tecnicas de controle. Um ESP Neural, treinado a partir de um conjunto de controladores lineares locais, e utilizado para investigar em quais regioes de operacao do sistema eletrico o desempenho do estabilizador a parâmetros fixos e deteriorada. O melhor desempenho do ESP Neural nessas regioes de operacao, quando comparado com o ESP convencional, e demonstrado atraves de simulacoes digitais nao-lineares de um sistema do tipo maquina sincrona conectada a um barramento infinito e de um sistema com quatro geradores.

Power system stabilizer scheduled by a fuzzy logic based supervisor from a local compensator network

This work presents a digital adaptive power system stabilizer (PSS) which operates in a gain scheduling scheme. Its parameters are designed for several differently selected operating points in a PxQ plane (active and reactive powers), and saved offline under the form of a look-up table in the microcomputer that implements the control action. The complete set of all designed PSSs is called a local compensator network (LCN). During working, the a fuzzy logic based supervisor identifies the current operating point, and synthesizes the PSS parameters from the LCN. The test presented shows good performance for this PSS, when compared to a conventional (nonadaptive) one.

Robust decentralized controller for minimizing coupling effect in single inductor multiple output DC-DC converter operating in continuous conduction mode

This paper describes a novel robust decentralized control design methodology for a single inductor multiple output (SIMO) DC-DC converter. Based on a nominal multiple input multiple output (MIMO) plant model and performance requirements, a pairing input-output analysis is performed to select the suitable input to control each output aiming to attenuate the loop coupling. Thus, the plant uncertainty limits are selected and expressed in interval form with parameter values of the plant model. A single inductor dual output (SIDO) DC-DC buck converter board is developed for experimental tests. The experimental results show that the proposed methodology can maintain a desirable performance even in the presence of parametric uncertainties. Furthermore, the performance indexes calculated from experimental data show that the proposed methodology outperforms classical MIMO control techniques.

MIMO filtered positional generalized predictive controller design for handling offset

The purpose of this paper is to present an alternative synthesis for the Generalized Predictive Controller (GPC) applied to a multiple-input multiple-output (MIMO) model, using both a positional plant model and cost function to deal with reference tracking, disturbance rejection and model-plant mismatch (MPM) with minimum control energy and closed-loop robustness. This new control design called Multivariable Filtered Positional GPC (MFP-GPC) uses an integral polynomial weighting filter for the setpoint and output of the plant, thereby extending the applicability of the predictive controllers. Additionally, robustness aspects are incorporated into the control design of the weighting polynomials, and this implementation involves the filter tuning parameters using a multi-objective optimization algorithm. Numerical simulations for a hydroelectric power and a methanol/water distillation plants show the effectiveness of the proposed control methodology.