Digital approaches

IEEE Trans. Ind. Electron.

et al. 2007

122

Abstract-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.Index Terms-Autonomous vehicles, embedded systems, fieldprogrammable gate arrays (FPGAs), fuzzy control, intellectual property (IP).

Section: Hw/sw Implementation Of Fuzzy Controllersmentioning

confidence: 99%

FPGA Implementation of Embedded Fuzzy Controllers for Robotic Applications

Sánchez-Solano

Cabrera

IEEE Trans. Ind. Electron.

et al. 2007

122

“…The other approach is to employ a fuzzy processor that cooperates with the main processor or works alone. Companies such as Togai InfraLogic, Toshiba, Siemens, Omron, and ST Microelectronics launched this kind of coprocessors in the 90s [8]- [9]. Recent research in this area can be seen in [4] and [10].…”

Section: Introductionmentioning

confidence: 99%

Design of Embedded DSP-Based Fuzzy Controllers for Autonomous Mobile Robots

IEEE Trans. Ind. Electron.

Moreno-Velo

Blanco

et al. 2008

Abstract-Fuzzy controllers are used in many applications because of their rapid design by translating heuristic knowledge, robustness against perturbations, and smoothness in the control action. However, they require parallel processing and special operators (such as fuzzification or defuzzification) which are not available at standard digital signal processors (DSPs), thus complicating its direct implementation. This paper describes an efficient design methodology which allows starting with any kind of fuzzy controller and subsequently transforming it until obtaining a system suitable for an easy DSP implementation. Such methodology is greatly aided by the design environment Xfuzzy 3. The parking problem of an autonomous robot is described to illustrate the steps of this methodology. Real experiments with the autonomous robot ROMEO 4R demonstrate the efficiency of the designed fuzzy controller embedded into a stand-alone card based on a fixed-point DSP from Texas Instruments.

“…In addition, the use of particular fuzzy operators such as minimum and maximum, Gaussian membership functions, which requires exponential calculus, and/or defuzzification methods that require to sweep the output universe of discourse may increase the computational cost of the system. In order to overcome the limitations of standard processors, two main approaches can be applied: (a) to expand the processor with a set of dedicated fuzzy logic instructions [4][5][6] and (b) to employ a fuzzy coprocessor (external or internal) that cooperate with the main processor [7][8][9].…”

mentioning

confidence: 99%

Embedded fuzzy controllers on standard DSPs

Proceedings of the IEEE International Symposium on Industrial Electronics, 2005. ISIE 2005.

Moreno-Velo²,

Sánchez-Solano³

et al. 2005

Fuzzy controllers are used in many applications because of their rapid design by translating heuristic knowledge, robustness against perturbations, and smoothness in the control action. However, they require parallel processing and special operators (such as fuzzification or defuzzification) which are not available at standard DSPs, thus making inefficient its direct implementation. This paper describes a design methodology which allows starting with any kind of fuzzy controller and subsequently transforming it until obtaining a system suitable for DSP implementation. Such methodology is aided by Xfuzzy 3, a design environment developed by some of the authors. The parking problem of an autonomous robot is described to illustrate the steps of this methodology. Experimental results show the efficiency of the designed fuzzy controller embedded into a stand-alone card based on a fixed-point DSP from Texas Instruments.