Julio Viola

Optimum Space Vector Computation Technique for Direct Power Control

This study presents an efficient control technique for computing the optimum space-vector voltage in power converters. The presented optimized direct power control (ODPC) provides a closed-form formula for the converter space-vector voltage, which, based on Lagrange operators for the optimum trajectory, provides the commanded complex apparent power. The voltage required by the ODPC is obtained with a standard modulation that synthesizes the mean value required during the control cycle. The converters performance using the ODPC algorithm improves over existing DPC-based algorithms that use constrained optimization, such as preselected space vectors or switching tables, by providing a further harmonic in content reduction, lower computational requirements, and faster time response to changes in active and reactive power commands. The use of the ODPC results in an almost instantaneous active and reactive power reference tracking, allowing for full power inversion in less than 1.0 ms under constant switching operation. Simulation results and experimental verifications are presented to validate the advantages of the proposed control algorithm. The scope of applications of this technique is those that require low harmonic impact on the ac power supply and for power quality improvement in general.

A Simple Switch Selection State for SVM Direct Power Control

This work presents a simple scheme for vector selection in direct power control (DPC) in a three-phase rectifier without the use of switch selection tables. The method is simulated using a C language description of the system and its results are later verified on an experimental test rig. Additional states are obtained using space vector modulation (SVM) which reduce the hysteresis band of the active and reactive power controller

Direct Power Control of a Dual Converter Operating as a Synchronous Rectifier

This paper presents a dual converter employed as a rectifier with power factor regulation and bidirectional power flow. The active and reactive powers flowing into the converter is controlled using an optimized direct-power-control algorithm. The multilevel structure of the converter is exploited to control the voltage level in each subconverter by selecting the modulation method from one commonly found in the literature, with the option of clamping one of the subconverters. These modulation methods are used to control the power taken by each subconverter, providing limited dc-link voltage regulation. The system is first simulated in SIMULINK, and the results are experimentally validated using a digital-signal-processor-based test rig.

A Flexible Hardware Platform for Applications in Power Electronics Research and Education

This work presents the design and development of a three-phase multilevel hardware platform for applications in power electronics. The emphasis of the proposed converter is in its flexibility to allow rapid set-ups of different experiments typically required in power electronics teaching and research. The proposed converter uses a cascaded H-bridge topology whereby multilevel operation with up to 9 voltage levels can be obtained. The selected power stage topology as well as the control, drivers and sensors boards designs, enable the platform to operate in multiple configurations, namely as inverter, controlled rectifier or active power filter, for one, two or three-phase systems.

Algorithm evaluation for the optimal selection of the space vector voltage using DPC in power systems

This work presents the experimental evaluation for a new scheme of optimal vector selection (OVS) in direct power control (DPC) for a three-phase rectifier without the use of switch selection tables. The OVS is physically implemented using a software configurable test rig (Platform III). Additional states were added to the standard seven space vectors obtained with a three-phase inverter bridge using space vector modulation (SVM) in order to reduce the hysteresis band of the power controller. Normal operation, model parameter fit, regenerative behavior and comparisons between two different sets of vectors are analyzed.

Direct Torque Control of Induction Motors Using a Fuzzy Inference System for Reduced Ripple Torque and Current Limitation

In this work a fuzzy inference system is employed for the control of a PWM based direct torque control (DTC), driving an induction machine, to reduce ripple torque while limiting the current during start-up or when the stator flux magnitude changes. The proposed control scheme uses a fuzzy inference system to modulate the stator voltage vector applied to the induction motor, in magnitude and phase. This scheme allows for amplitude regulation according to the requirements of ripple reduction or stator current limitation. The proposed scheme performance was analyzed using simulation programs written in the C computer language and executed on a prototype system called PLATAFORMA III, developed by the SIEP Group at Universidad Simon Bolivar

Direct torque control of induction motors using fuzzy logic with current limitation

This work presents a DTC system controlled by a fuzzy logic system that also limits the stator current. The simulation and experimental results are presented for two different stator current limitation strategies. The proposed control scheme uses the fuzzy logic controller to modulate the voltage vector phase applied to the induction motor. This scheme keeps the control voltage vector magnitude almost constant, allowing variations only to limit the stator current. The proposed scheme performance was analyzed using simulation programs written in the C computer language, and the simulated predictions were validated with experimental measurements obtained using a 1 1/2 HP motor driven by a rectifier-inverter system called plataforma, developed by the SIEP Group at Simon Bolivar University.

Simplified Control Structure for Current Control of Single Phase Rectifiers Using COT-ANN-PWM

This paper describes a single phase switched rectifier for current control using model reference adaptive control (MRAC) with a continually on-line trained artificial neural network (COT-ANN). The results obtained with the proposed scheme are similar to the ones obtained in a previous work but using a simpler control structure. Simulations are used to test the validity of the proposed algorithm and the results are later verified by a practical implementation of this system.

Model of the induction machine including saturation

This work proposes a model for induction machines in natural coordinates “abc”, developed considering the nonlinear characteristics of saturation. Traditionally, the models for the induction machine including this effect make use of linear transformations. However, the nonlinearity of saturation does not allow the use of these transformations, giving invalid results. Flux linkage in each phase leads to the saturation coefficient and this to the magnetic permeance. Hence, the saturation coefficient produces a new inductance in natural coordinates that considers the nonlinearity of saturation. The machine behavior is computed using a state variable model in natural coordinates described in the space vector frame. The results obtained by the proposed model give a better harmonic representation than the “dq0”models obtained by neglecting the magnetic hysteresis effect. A comparison between the proposed representation and the traditional one shows the advantages of the former.

PLATAFORMA: A useful tool for high level education, research and development

This work presents the PLATAFORMA system impact over the teaching and research activities of the lecturers and the post graduate students at Master and Doctorate levels working in the Power Electronics Industrial Systems group (Grupo de Sistemas Industriales de Electronica de Potencia, SIEP) of the Universidad Simon Bolivar. PLATAFORMA is an integrated test system intended for experiments requiring validation of different types of new strategies and control schemes, based on vector control theories, parametric estimation, neural networks and fuzzy logic control systems, applied to machine drives, and it can be also used for analyzing the effect of these control strategies over the mains quality. The equipment includes driver power stages, an instrumentation stage and a signal processing and control stage. PLATAFORMA has eliminated most of the tedious work that every single researcher or post graduate student in the GSIEP group had to do in order to obtain experimental results, enhancing the quality of the thesis and papers produced by the group members.