Design and Implementation of Ga-Based Fuzzy System on Fpga Chip

Abstract

In this article, a design and implementation methodology of a GA-based fuzzy system on a Field Programmable Gate Array (FPGA) chip is proposed. First, a self-generating method based on a genetic algorithm (GA) is proposed to automatically construct a high performance fuzzy system. Some simulation results of an inverted pendulum control system are presented to illustrate the efficiency of the proposed GA-based method in the fuzzy system design. Then, a fuzzy system design method by using VHSIC Hardware Description Language (VHDL) is proposed so that the fuzzy system hardware implemented on an FPGA chip has a great flexibility and a high process speed. Moreover, a friendly-used software tool is developed to automatically generate VHDL codes for the users to easily design their fuzzy system hardware based on the proposed methodology. Finally, some experimental results are presented to illustrate the validity and the applicability of the design methodology.

Building Information Modeling using Hardware Genetic Algorithms with Field-Programmable Gate Arrays

“…Recent advances on field-programmable gate arrays employing GA have gained insights on implementation, effectiveness and practicality of this technique. (Wong, & Lin, 2008) showed fundamental results on how a GA-fuzzy system can be implemented on a fieldprogrammable gate arrays chip. A simulated inverted pendulum was employed to show the effectiveness of their method.…”

FPGA realisation of inverse kinematics for biped robot based on CORDIC

“…Some CORDIC designs have been implemented on a field programmable gate array (FPGA) chip [2,3], such as mobile robot exploration [4] and kinematics control for a manipulator [5]. The FPGA-based system is useful because it can reduce development time, reprogrammed on the fly, and operate faster than a microprocessor [6]. However, there is no research related to the FPGA realisation of inverse kinematics for a biped robot based on CORDIC.…”