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This paper describes the hardware and software modules of a remote Internet-based laboratory for experimentation with a 120-kVA multilevel power converter. The key feature of this laboratory is the utilization of a multilevel converter that can be controlled and supervised remotely in a secured way. A wide variety of laboratory experiments are supported, from grid connection to ac motor control. Users can choose the control structure, the control parameters, and the kind of load and get the graphical results of the measurements, all in real time. Index Terms--Multilevel power converters, real-time control, remote laboratory.

This paper introduces a new adaptive notch filtering approach to extract the harmonic and reactive current components for power quality purposes in grid-connected converters. The main function of this method is to provide synchronized harmonic and reactive current components for control purposes. The theoretical analysis is presented, and the performance of the method is experimentally evaluated. The methodology is applicable for a wide range of equipment such as uninterrupted power supplies, regenerative converters, active power filters, etc., as a basis for generating the reference signals. Index Terms--Active power filters, adaptive filters, harmonics and reactive power compensation.

An electric machine submitted to dissipations and a too high temperature can generate irreversible damage. A reduced thermal model allows us to monitor the critical points of the machine. The thermal modeling of the machine adopted here results from the association of two methods: a nodal approach which models the diffusion in the structure and a computational fluid dynamics (CFD) approach which characterizes the convective heat exchanges which operate in the end cavities. A methodology of reduction is proposed and applied to the thermal model of a 5.5-kW two-pole induction machine to obtain a reduced four-node model for real-time thermal monitoring. Index Terms--Electric machines, identification, model reduction, thermal modeling.

This paper discusses the control and implementation of a real-time spotting system. It is intended for high-density high-yield microarray fabrication to facilitate diagnostic and research effort in genomics and proteomics. The method is based on a self-sensing fully automated aspiring/dispensing pin. System performance is evaluated by several batch runs with deionized water solutions of 0.3% fluorescent Cy-3 dye, which has similar physical properties to the deoxyribonucleic acid (DNA) probe materials. Experimental results show that this system is capable of fast and robust DNA/protein microarray fabrication in high volume while keeping spot size as small as 60 [micro]m consistently. Based on the laser scanned images and experimental data of the spotted microarrays, it is also verified that this system can recognize and prevent the formation of abnormal spots. Index Terms--Control, microarray, protein, real time, spotting.

This paper presents and analyzes experimental results of a new discrete multiloop nonlinear control scheme, applied to a 1.5-kW laboratory prototype of a three-phase/level/switch boost-type Vienna rectifier. As for most split dc-bus voltage switched-mode rectifiers, the proposed control technique aims to ensure ac line currents shaping, output dc-bus voltage regulatioand dc load unbalance compensation. The proposed technique is based on the dq nonlinear averaged model of the converter. To cancel the inherent nonlinearity of the converter, an input-to-output transform is applied to both inner and outer loops, thus linearizing the system and allowing the application of conventional linear pole placement method for controller tuning. The rectifier performance, during both nominal and severe operating conditions, are then evaluated in real-time using the dSPACE DS 1104 controller board, supported by a Matlab/Simulink Real-Time Workshop environment. Index Terms--High power factor, low ac current total harmonic distortion (THD), nonlinear systems, real-time control, threephase/switch/level rectifier.

In this paper, we implement the intelligent neural network controller hardware with a field programmable gate array (FPGA)-based general purpose chip and a digital signal processing (DSP) board to solve nonlinear system control problems. The designed intelligent control hardware can perform real-time control of the backpropagation learning algorithm of a neural network. The basic proportional-integral-derivative (PID) control algorithms are implemented in an FPGA chip and a neural network controller is implemented in a DSP board. By using a high capacity of an FPGA chip, the additional hardware such as an encoder counter and a pulsewidth modulation (PWM) generator is implemented in a single FPGA chip. As a result, the controller becomes cost effective. It was tested for controlling nonlinear systems such as a robot finger and an inverted pendulum on a moving cart to show performance of the controller. Index Terms--Digital signal processing (DSP), field programmable gate array (FPGA), inverted pendulum, neural network controller, proportional-integral-derivative (PID) controller, robot finger.