4,256 research outputs found
Modeling and Design of Digital Electronic Systems
The paper is concerned with the modern methodologies for holistic modeling of electronic systems enabling system-on-chip design. The method deals with the functional modeling of complete electronic systems using the behavioral features of Hardware Description Languages or high level languages then targeting programmable devices - mainly Field Programmable Gate Arrays (FPGAs) - for the rapid prototyping of digital electronic controllers. This approach offers major advantages such as: a unique modeling and evaluation environment for complete power systems, the same environment is used for the rapid prototyping of the digital controller, fast design development, short time to market, a CAD platform independent model, reusability of the model/design, generation of valuable IP, high level hardware/software partitioning of the design is enabled, Concurrent Engineering basic rules (unique EDA environment and common design database) are fulfilled. The recent evolution of such design methodologies is marked through references to case studies of electronic system modeling,simulation, controller design and implementation. Pointers for future trends / evolution of electronic design strategies and tools are given
FPGA design methodology for industrial control systems—a review
This paper reviews the state of the art of fieldprogrammable gate array (FPGA) design methodologies with a focus on industrial control system applications. This paper starts with an overview of FPGA technology development, followed by a presentation of design methodologies, development tools and relevant CAD environments, including the use of portable hardware description languages and system level programming/design tools. They enable a holistic functional approach with the major advantage of setting up a unique modeling and evaluation environment for complete industrial electronics systems. Three main design rules are then presented. These are algorithm refinement, modularity, and systematic search for the best compromise between the control performance and the architectural constraints. An overview of contributions and limits of FPGAs is also given, followed by a short survey of FPGA-based intelligent controllers for modern industrial systems. Finally, two complete and timely case studies are presented to illustrate the benefits of an FPGA implementation when using the proposed system modeling and design methodology. These consist of the direct torque control for induction motor drives and the control of a diesel-driven synchronous stand-alone generator with the help of fuzzy logic
Deep Space Network information system architecture study
The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control
Open FPGA-based development platform for fuzzy systems with applications to communications
Soft computing techniques are gaining momentum as tools
for network traffic modeling, analysis and control. Efficient
hardware implementations of these techniques that can
achieve real-time operation in high-speed communications
equipment is however an open problem. This paper describes
a platform for the development of fuzzy systems with applications
to communications systems, namely network traffic
analysis and control. An FPGA development board with PCI
interface is employed to support an open platform that comprises
open CAD tools as well as IP cores. For the development
process, we set up a methodology and a CAD tools
chain that cover from initial specification in a high-level language
to implementation on FPGA devices. PCI compatible
fuzzy inference modules are implemented as SoPC based on
the open WISHBONE interconnection architecture. We outline
results from the design and implementation of fuzzy analyzers
and regulators for network traffic. These systems are
shown to satisfy operational and architectural requirements
of current and future high-performance routing equipment.Ministerio de Educación y Ciencia TEC2005-04359/MICJunta de Andalucía TIC2006-63
A design environment for synthesis of embedded fuzzy controllers on FPGAs
This paper presents a design environment for the
synthesis of embedded fuzzy controllers on FPGAs. It provides
a novel implementation technique that allows accelerating the
exploration of the design space of fuzzy control modules, as
well as a codesign flow that eases their integration into complex
control systems and the joint development of hardware and
software components. The set of CAD tools supporting this
environment includes specific fuzzy logic design tools provided
by Xfuzzy, FPGA synthesis and implementation tools from
Xilinx, and modeling and simulation facilities from Matlab. As
demonstrated by the analyzed design examples, the described
development strategy takes advantage of flexibility and ease of
configuration offered by the different tools to dramatically
speed up the stages of description, synthesis, and functional
verification of embedded fuzzy control system
Design and Development of Industrial Systems for Guidance and Control of Marine Surface Vessels
This paper discusses the design and development of industrial systems for guidance and control of marine surface vessels. In order to cover the large area of industrial marine guidance and control, focus has been given on the relatively high-level physical and logical design issues that dictate system capabilities, justified by a holistic view on GNC (Guidance, Navigation, and Control) systems. This project makes an effort to achieve this goal by structuring and categorizing the industrial systems and relating them to the academic framework found in the academic literature. This paper focuses on industrial methods of GNC and multi sensor monitoring system. Throughout this paper, an effort is made to relate issues, technical and safety wise to international regulations and standards in order to ensure realistic premises. The findings of this project are expected to be useful on developing remotely control self-navigated surface vessel which then could revolutionize the way of deploying and supporting underwater vehicle operation
FPGAs in Industrial Control Applications
The aim of this paper is to review the state-of-the-art of Field Programmable Gate Array (FPGA) technologies and their contribution to industrial control applications. Authors start by addressing various research fields which can exploit the advantages of FPGAs. The features of these devices are then presented, followed by their corresponding design tools. To illustrate the benefits of using FPGAs in the case of complex control applications, a sensorless motor controller has been treated. This controller is based on the Extended Kalman Filter. Its development has been made according to a dedicated design methodology, which is also discussed. The use of FPGAs to implement artificial intelligence-based industrial controllers is then briefly reviewed. The final section presents two short case studies of Neural Network control systems designs targeting FPGAs
Using Building Blocks to Design Analog Neuro-Fuzzy Controllers
We present a parallel architecture for fuzzy controllers and a methodology for their realization as analog CMOS chips for low- and medium-precision applications. These chips can be made to learn through the adaptation of electrically controllable parameters guided by a dedicated hardware-compatible learning algorithm. Our designs emphasize simplicity at the circuit level—a prerequisite for increasing processor complexity and operation speed. Examples include a three-input, four-rule controller chip in 1.5-μm CMOS, single-poly, double-metal technology
Hardware/software codesign of configurable fuzzy control systems
Fuzzy inference techniques are an attractive and well-established approach for solving control problems. This is mainly
due to their inherent ability to obtain robust, low-cost controllers from the intuitive (and usually ambiguous or incomplete)
linguistic rules used by human operators when describing the control process. This paper focuses on the hardware/software
codesign of configurable fuzzy control systems. Two prototype systems implemented on general-purpose development boards
are presented. In both of them, hardware components are based on specific and configurable fuzzy inference architecture
whereas software tasks are supported by a microcontroller. The first prototype uses an off-the-shelf microcontroller and a
low-complexity Xilinx XC4005XL field programmable gate array (FPGA). The second one is implemented as a system on
programmable chip (SoPC), integrating the microcontroller together with the fuzzy hardware architecture and its interface
circuits into a Xilinx Spartan2E200 FPGA.Comisión Interministerial de Ciencia y Tecnología TIC2001-1726-C02-0
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