542 research outputs found
A comparison of various double loops frequency selective surfaces in terms of angular stability
This paper presents the comparison of
Frequency Selective Surfaces (FSS) structure performance
based on three different double loops: square, circular and
hexagonal structures. The simulation process of the double loops
FFS structures are carried out by using the Computer
Simulation Technology (CST) Microwave Studio software. The
dielectric substrate used in the simulation is the FR-4 lossy
substrate
Embedded electronic systems driven by run-time reconfigurable hardware
Abstract
This doctoral thesis addresses the design of embedded electronic systems based on run-time reconfigurable hardware technology –available through SRAM-based FPGA/SoC devices– aimed at contributing to enhance the life quality of the human beings. This work does research on the conception of the system architecture and the reconfiguration engine that provides to the FPGA the capability of dynamic partial reconfiguration in order to synthesize, by means of hardware/software co-design, a given application partitioned in processing tasks which are multiplexed in time and space, optimizing thus its physical implementation –silicon area, processing time, complexity, flexibility, functional density, cost and power consumption– in comparison with other alternatives based on static hardware (MCU, DSP, GPU, ASSP, ASIC, etc.). The design flow of such technology is evaluated through the prototyping of several engineering applications (control systems, mathematical coprocessors, complex image processors, etc.), showing a high enough level of maturity for its exploitation in the industry.Resumen
Esta tesis doctoral abarca el diseño de sistemas electrĂłnicos embebidos basados en tecnologĂa hardware dinámicamente reconfigurable –disponible a travĂ©s de dispositivos lĂłgicos programables SRAM FPGA/SoC– que contribuyan a la mejora de la calidad de vida de la sociedad. Se investiga la arquitectura del sistema y del motor de reconfiguraciĂłn que proporcione a la FPGA la capacidad de reconfiguraciĂłn dinámica parcial de sus recursos programables, con objeto de sintetizar, mediante codiseño hardware/software, una determinada aplicaciĂłn particionada en tareas multiplexadas en tiempo y en espacio, optimizando asĂ su implementaciĂłn fĂsica –área de silicio, tiempo de procesado, complejidad, flexibilidad, densidad funcional, coste y potencia disipada– comparada con otras alternativas basadas en hardware estático (MCU, DSP, GPU, ASSP, ASIC, etc.). Se evalĂşa el flujo de diseño de dicha tecnologĂa a travĂ©s del prototipado de varias aplicaciones de ingenierĂa (sistemas de control, coprocesadores aritmĂ©ticos, procesadores de imagen, etc.), evidenciando un nivel de madurez viable ya para su explotaciĂłn en la industria.Resum
Aquesta tesi doctoral estĂ orientada al disseny de sistemes electrònics empotrats basats en tecnologia hardware dinĂ micament reconfigurable –disponible mitjançant dispositius lògics programables SRAM FPGA/SoC– que contribueixin a la millora de la qualitat de vida de la societat. S’investiga l’arquitectura del sistema i del motor de reconfiguraciĂł que proporcioni a la FPGA la capacitat de reconfiguraciĂł dinĂ mica parcial dels seus recursos programables, amb l’objectiu de sintetitzar, mitjançant codisseny hardware/software, una determinada aplicaciĂł particionada en tasques multiplexades en temps i en espai, optimizant aixĂ la seva implementaciĂł fĂsica –à rea de silici, temps de processat, complexitat, flexibilitat, densitat funcional, cost i potència dissipada– comparada amb altres alternatives basades en hardware estĂ tic (MCU, DSP, GPU, ASSP, ASIC, etc.). S’evalĂşa el fluxe de disseny d’aquesta tecnologia a travĂ©s del prototipat de varies aplicacions d’enginyeria (sistemes de control, coprocessadors aritmètics, processadors d’imatge, etc.), demostrant un nivell de maduresa viable ja per a la seva explotaciĂł a la indĂşstria
Design and Implementation of ANFIS Algorithm Using VHDL for Vechicular System
In this review paper Field Programmable Gate Array (FPGA) is proposed to build an Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm for non linear behavior of the system. In the application of designing the algorithm for controlling a full vehicle nonlinear active suspension system. The algorithm for neural was Back propagation and for fuzzy takagi- sugeno-kang active suspension systems is very important for guaranteeing the riding comfort for passengers and road handling quality for a vehicle. It is shown that the ANFIS can modelize a nonlinear system very accurately by means of data taken from mathematical model. Firstly the MATLAB SIMULINK toolboxes are used to simulate the proposed controllers with the controlled model and to display the responses of the controlled model under different types of disturbance. But in this paper the implementation of the adaptive neuro fuzzy inference system algorithm using FPGA boards has been try to investigated in this work. The Xilinx ISE software is employed to synthesis the VHDL codes used to program the FPGA.
DOI: 10.17762/ijritcc2321-8169.15028
XFVHDL4: A hardware synthesis tool for fuzzy systems
This paper presents a design technique that allows the automatic synthesis of fuzzy inference systems and accelerates the exploration of the design space of these systems. It is based on generic VHDL code generation which can be implemented on a programmable device (FPGA) or an application specific integrated circuit (ASIC). The set of CAD tools supporting this technique includes a specific environment for designing fuzzy systems, in combination with commercial VHDL simulation and synthesis tools. As demonstrated by the analyzed design examples, the described development strategy speeds up the stages of description, synthesis, and functional verification of fuzzy inference systems.Comunidad Europea FP7-IST-248858Ministerio de Ciencia e InnovaciĂłn TEC2008-04920Junta de AndalucĂa P08-TIC-0367
Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles
The combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Some of the results presented in this work are related to activities within the 3Ccar project, which has
received funding from ECSEL Joint Undertaking under grant agreement No. 662192. This Joint Undertaking
received support from the European Union’s Horizon 2020 research and innovation programme and Germany,
Austria, Czech Republic, Romania, Belgium, United Kingdom, France, Netherlands, Latvia, Finland, Spain, Italy,
Lithuania. This work was also partly supported by the project ENABLES3, which received funding from ECSEL
Joint Undertaking under grant agreement No. 692455-2
Advanced control system for stand-alone diesel engine driven-permanent magnetic generator sets
The main focus is on the development of an advanced control system for variable speed standalone
diesel engine driven generator systems.
An extensive literature survey reviews the historical development and previous relevant
research work in the fields of diesel engines, electrical machines, power electronic converters,
power and electronic systems. Models are developed for each subsystem from mathematical
derivations with necessary simplifications made to reduce complexity while retaining the
required accuracy. Initially system performance is investigated using simulation models in
Matlab/Simulink.
The AC/DC/AC power electronic conversion system used employs a voltage controlled dc
link. The ac voltage is maintained at constant magnitude and frequency by using a dc-dc
converter and a fixed modulation ratio VSI PWM inverter. The DC chopper provides fast
control of the output voltage by dealing efficiently with transient conditions.
A Variable Speed Fuzzy Logic Core (VSFLC) controller is combined with a classical control
method to produce a novel hybrid controller. This provides an innovative variable speed
control that responds to both load and speed changes. A new power balance based control
strategy is proposed and implemented in the speed controller.
Subsequently a novel overall control strategy is proposed to co-ordinate the hybrid variable
speed controller and chopper controller to provide overall control for both fast and slow
variations of system operating conditions.
The control system is developed and implemented in hardware using Xilinx Foundation
Express. The VHDL code for the complete control system design is developed and the
designs are synthesised and analysed within the Xilinx environment. The controllers are
implemented with XC95108-PC84 and XC4010-PC84 to provide a compact and cheap control
system. A prototype experimental system is described and test results are obtained that show
the combined control strategy to be very effective. The research work makes contributions in
the areas of automatic control systems for diesel engine generator sets and CPLD/FPGA
application that will benefit manufacturers and consumers.EPSR
An FPGA Kalman-MPPT implementation adapted in SST-based dual active bridge converters for DC microgrids systems
The design of digital hardware controllers for the integration of renewable energy sources in DC microgrids is a research topic of interest. In this paper, a Kalman filter-based maximum power point tracking algorithm is implemented in an FPGA and adapted in a dual active bridge (DAB) converter topology for DC microgrids. This approach uses the Hardware/Software (HW/SW) co-design paradigm in combination with a pipelined piecewise polynomial approximation design of the Kalman-maximum power point tracking (MPPT) algorithm instead of traditional lookup table (LUT)-based methods. Experimental results reveal a good integration of the Kalman-MPPT design with the DAB-based converter, particularly during irradiation and temperature variations due to changes in weather conditions, as well as a good balanced hardware design in complexity and area-time performance compared to other state-of-art FPGA designs
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