Model-Based Design Methodology for Rapid Development of Fuzzy Controllers on FPGAs

The complexity reached by current applications of industrial control systems has motivated the development of new computational paradigms, as well as the employment of hybrid implementation techniques that combine hardware and software components to fulfill system requirements. On the other hand, continuous improvements in field-programmable devices today make possible the implementation of complex control systems on reconfigurable hardware, although they are limited by the lack of specific design tools and methodologies to facilitate the development of new products. This paper describes a model-based design approach for the synthesis of embedded fuzzy controllers on field-programmable gate arrays (FPGAs). Its main contributions are the proposal of a novel implementation technique, which allows accelerating the exploration of the design space of fuzzy inference modules, and the use of a design flow that eases their integration into complex control systems and the joint development of hardware and software components. This design flow is supported by specific tools for fuzzy systems development and standard FPGA synthesis and implementation tools, which use the modeling and simulation facilities provided by the Matlab environment. The development of a complex control system for parking an autonomous vehicle demonstrates the capabilities of the proposed procedure to dramatically speed up the stages of description, synthesis, and functional verification of embedded fuzzy controllers for industrial applications.