SCALABLE ARCHITECTURE FOR HIGH-SPEED MULTIDIMENSIONAL FUZZY INFERENCE SYSTEMS

INÉS DEL CAMPO, JAVIER ECHANOBE, KOLDO BASTERRETXEA, GUILLERMO BOSQUE
2011 Journal of Circuits, Systems and Computers  
This paper presents a scalable architecture suitable for the implementation of high-speed fuzzy inference systems on reconfigurable hardware. The main features of the proposed architecture, based on the Takagi-Sugeno inference model, are scalability, high performance, and flexibility. A scalable Fuzzy Inference System (FIS) must be efficient and practical when applied to complex situations, such as multidimensional problems with a large number of membership functions and a large rule base.
more » ... al current application areas of fuzzy computation require such enhanced capabilities to deal with real-time problems (e.g. robotics, automotive control, etc.). Scalability and high performance of the proposed solution have been achieved by exploiting the inherent parallelism of the inference model, while flexibility has been obtained by applying Hardware/Software co-design techniques to reconfigurable hardware. Last generation reconfigurable technologies, particularly Field Programmable Gate Arrays (FPGAs), make it possible to implement the whole embedded FIS (e.g., processor core, memory blocks, peripherals, and specific hardware for fuzzy inference) on a single chip with the consequent savings in size, cost and power consumption. As a prototyping example, we implemented a complex fuzzy controller for a vehicle semi-active suspension system composed of four three-input FIS on a single FPGA of the Xilinx's Virtex 5 device family.
doi:10.1142/s0218126611007359 fatcat:5xcs5lscbfbshjhowix7fzosme