Hardware/software codesign methodology for fuzzy controller implementation

This paper describes a HW/SW codesign methodology for the implementation of fuzzy controllers on a platform composed by a general-purpose microcontroller and specific processing elements implemented on FPGAs or ASICs. The different phases of the methodology, as well as the CAD tools used in each design stage, are presented, with emphasis on the fuzzy system development environment Xfuzzy. Also included is a practical application of the described methodology for the development of a fuzzy controller for a dosage system

Controladores difusos adaptativos como módulos de propiedad intelectual para FPGAs

La continua demanda por parte del mercado microelectrónico de aplicaciones novedosas, con elevados niveles de complejidad y tiempos de desarrollo cortos ha motivado el impulso de las técnicas de diseño basadas en el concepto de “reusabilidad” y el desarrollo de elementos de sistemas como módulos de propiedad intelectual o módulos IP. En esta comunicación se describe la implementación de controladores difusos como módulos IP para FPGAs. Los controladores operan como periféricos conectables al bus OPB para los procesadores disponibles en las FPGAs de Xilinx. El empleo de las memorias internas de las FPGAs para almacenar las bases de conocimiento permite definir o ajustar la funcionalidad en tiempo de operación.Ministerio de Educaión y Ciencia TEC2005-04359/MI

FPGA implementation of embedded fuzzy controllers for robotic applications

Fuzzy-logic-based inference techniques provide efficient solutions for control problems in classical and emerging applications. However, the lack of specific design tools and systematic approaches for hardware implementation of complex fuzzy controllers limits the applicability of these techniques in modern microelectronics products. This paper discusses a design strategy that eases the implementation of embedded fuzzy controllers as systems on programmable chips. The development of the controllers is carried out by means of a reconfigurable platform based on field-programmable gate arrays. This platform combines specific hardware to implement fuzzy inference modules with a general-purpose processor, thus allowing the realization of hybrid hardware/soffivare solutions. As happens to the components of the processing system, the specific fuzzy elements are conceived as configurable intellectual property modules in order to accelerate the controller design cycle. The design methodology and tool chain presented in this paper have been applied to the realization of a control system for solving the navigation tasks of an autonomous vehicle

FPGA Implementation of Embedded Fuzzy Controllers for Robotic Applications

Fuzzy-logic-based inference techniques provide efficient solutions for control problems in classical and emerging applications. However, the lack of specific design tools and systematic approaches for hardware implementation of complex fuzzy controllers limits the applicability of these techniques in modern microelectronics products. This paper discusses a design strategy that eases the implementation of embedded fuzzy controllers as systems on programmable chips. The development of the controllers is carried out by means of a reconfigurable platform based on field-programmable gate arrays. This platform combines specific hardware to implement fuzzy inference modules with a general-purpose processor, thus allowing the realization of hybrid hardware/software solutions. As happens to the components of the processing system, the specific fuzzy elements are conceived as configurable intellectual property modules in order to accelerate the controller design cycle. The design methodology and tool chain presented in this paper have been applied to the realization of a control system for solving the navigation tasks of an autonomous vehicle. © 2007 IEEE.Ministerio de Educación y Ciencia TEC2005-04359/MIC y DPI2005-02293Junta de Andalucía TIC2006-635 y TEP2006-37

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

Hardware/Software Co-Design of a Fuzzy RISC Processor

In this paper, we show how hardware/software coevaluation can be applied to instruction set definition. As a case study, we show the definition and evaluation of instruction set extensions for fuzzy processing. These instructions are based on the use of subword parallelism to fully exploit the processor's resources by processing multiple data streams in parallel. The proposed instructions are evaluated in software and hardware to gain a balanced view of the costs and benefits of each instruction. We have found that a simple instruction optimized to perform fuzzy rule evaluation offers the most benefit to improve fuzzy processing performance