This brief proposes an adaptation of the Generalized Predictive Control (GPC) for ramp-reference tracking. The second-order difference operation and the plant model are used to get an augmented model with two embedded integrators and whose output is the tracking error. Differently from other GPC-based tracking algorithms, the proposed approach does not require information about the reference parameters, and the GPC prediction horizon is composed of the predicted errors instead of the expected plant outputs. Thus, the optimization function and the receding horizon strategy used in conventional GPC can be applied to get the control law. Simulation and experimental results prove that the proposed approach can successfully track constant and ramp references. The proposed method is applicable for single-input single-outputs plants. However, the mathematical background presented in this brief can be used in the development of new GPC strategies.

The problem of signal tracking, in the presence of a disturbance signal in the plant, is solved using a zero-variation methodology. A state feedback controller is designed in order to minimise the ℋ₂-norm of the closed-loop system, such that the effect of the disturbance is attenuated. Then, a state estimator is designed and the modification of the zeros is used to minimise the ℋ_∞-norm from the reference input signal to the error signal. The error is taken to be the difference between the reference and the output signals, thereby making it a tracking problem. The design is formulated in a linear matrix inequality framework, such that the optimal solution of the stated control problem is obtained. Practical examples illustrate the effectiveness of the proposed method.

The fluorescent lamp lifetime is very dependent of the start-up lamp conditions. The lamp filament current and temperature during warm-up and at steady-state operation are important to extend the life of a hot-cathode fluorescent lamp, and the preheating circuit is responsible for attending to the start-up lamp requirements. The usual solution for the preheating circuit used in self-oscillating electronic ballasts is simple and presents a low cost. However, the performance to extend the lamp lifetime is not the most effective. This paper presents an effective preheating circuit for self-oscillating electronic ballasts as an alternative to the usual solution.

Some important applications require control systems capable of tracking high-degree polynomial references. However, polynomial reference tracking is difficult because the controller must have a fast response to track variable references. Generalized Predictive Control (GPC), used in industrial applications, has a fast response. However, up to now, GPC approaches in the literature are not designed for high-degree polynomial reference tracking. For that reason, this brief proposes a GPC system for the tracking of polynomial references of any degree. The high-order backward difference operator was used to develop an augmented prediction model designed to have an arbitrary number of embedded integrators. Thus, according to the internal model principle, the proposed predictive controller can track polynomial references of any degree. An optimization technique is used to define future control actions, while the control law is defined through the receding horizon principle. Simulation and experimental results prove that the proposed controller performs better than other approaches described in the literature.

This work proposes a design methodology for predictive control applied to the single-phase PWM inverter with an LC filter. In the design, we considered that the PWM inverter has parametric uncertainties in the filter inductance and output load resistance. The control system purpose is to track a sinusoidal signal at the inverter output. The designed control system with an embedded integrator uses the principle of receding horizon control, which underpinned predictive control. The methodology was described by linear matrix inequalities, which can be solved efficiently using convex programming techniques, and the optimal solution is obtained. MATLAB-Simulink and real-time FPGA-in-the-loop simulations illustrate the viability of the proposed control system. The LMI-based MPC reveals an effective performance for tracking of a sinusoidal reference signal and disturbance rejection of input voltage and load perturbations for the inverter subject to uncertainties.

Este trabalho apresenta uma solução para a detecção de faltas de alta impedância (FAIs) por meio do uso de um dispositivo FPGA (Field Programmable Gate Array). A proposição é de vital importância para o funcionamento adequado do sistema elétrico de distribuição de forma a atender aos requisitos dos procedimentos de distribuição (PRODIST), elaborados pela Agência Nacional de Energia Elétrica (ANEEL). Para analisar o comportamento das grandezas elétricas frente a essa falha, uma rede de distribuição primária foi modelada, usando a plataforma MATLAB/Simulink®. Paralelamente à modelagem, um algoritmo em linguagem VHDL (VHSIC Hardware Description Language) foi desenvolvido para a detecção da falta, no qual o monitoramento da corrente fasorial, por meio da Transformada Discreta de Fourier, foi utilizado, além do valor RMS da corrente de sequência zero. Para realizar as simulações e os testes do algoritmo, o software ModelSim® foi utilizado, e, posteriormente, o código foi embarcado no dispositivo de lógica programável FPGA. O algoritmo de detecção de falta de alta impedância foi integrado ao sistema modelado em Simulink® para monitoramento em tempo real e comando de um dispositivo de proteção. Os resultados apontam que o algoritmo foi capaz de detectar as faltas, indicando a fase interrompida e comandando a proteção de forma eficiente.