Hybrid System: A Smart Choice for Real Time Application

Saikat Mondal, Sudip Kumar Ghorui, Roshan Ghosh
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Abstract

Fuzzy logic based control system provides a simple and efficient method to control highly complex and imprecise situation. However, the lack of simple hardware designs that is the capable of implementing fuzzy controller's parameters in a single chip, sometimes limits the capability of fuzzy based system in an automotive and industrial environment. In present days, a reconfigurable hardware platform like field programmable gate array (FPGA) has become an alluring alternative to synthesis and implements the desired system with an appropriate design for automation tool. This paper aims to address different hardware implementation issues of fuzzy system on a real-time environment (FPGA) and also proposes the hardware friendly neuro-fuzzy technique as a better replacement of a fuzzy system. In this paper, a simple rule base has been realized on the Xilinx SPARTAN 3AN FPGA development board to bolster the feasibility and superiority of the neuro-fuzzy over the fuzzy system. For the purpose of hardware implementation, optimum choice in terms of speed, accuracy and resource utilization is obtained in case of neuro-fuzzy technique and the results are in conformation.
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混合系统:实时应用的明智选择
基于模糊逻辑的控制系统为控制高度复杂和不精确的情况提供了一种简单有效的方法。然而,由于缺乏能够在单个芯片上实现模糊控制器参数的简单硬件设计,有时会限制基于模糊的系统在汽车和工业环境中的能力。目前,像现场可编程门阵列(FPGA)这样的可重构硬件平台已经成为一种诱人的替代方案,并通过适当的自动化工具设计来实现所需的系统。本文旨在解决模糊系统在实时环境(FPGA)上的各种硬件实现问题,并提出硬件友好的神经模糊技术作为模糊系统的更好替代品。本文在Xilinx SPARTAN 3AN FPGA开发板上实现了一个简单的规则库,以增强神经模糊系统相对于模糊系统的可行性和优越性。从硬件实现的角度出发,对神经模糊技术在速度、精度和资源利用率方面进行了优化选择,结果一致。
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