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Co-Design Approach to Genetically Tuned Fuzzy Temperature Controller

机译:遗传优化模糊温度控制器的协同设计方法

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Since its inception fuzzy control has gained popularity in process parameter control. It has proven the potentiality in wide range of applications ranging from domestic appliances to industrial process control. The implementation of Fuzzy Control on real scale demands for Designing the Fuzzy Control though simple, it involves tedious tuning of membership functions and fuzzy inference rules. Many tuning techniques are being practiced, besides the tuning by Genetic Algorithm. The present paper reports the designing of Fuzzy Logic Temperature controller using Fuzzy Tool Box of MATLAB and interface linkage of furnace temperature sensor and thyristor based drive circuit forelectric bulb acting as a heating element of furnace via MATLAB simulink system model. The tuning of membership function is employed offline using Genetic Algorithm. The tuning and execution of software-hardware co-designed fuzzy logic temperature controller was successfully demonstrated. The results are obtained as expected towards optimizing the set-point temperature.
机译:自成立以来,模糊控制已在过程参数控制中得到普及。它已经证明了从家用电器到工业过程控制的广泛应用潜力。在实际规模上执行模糊控制对设计模糊控制的要求很简单,但是它涉及到隶属函数和模糊推理规则的繁琐调整。除了通过遗传算法进行调整以外,还正在实践许多调整技术。本文利用MATLAB的simulink系统模型,利用MATLAB的模糊工具箱设计了模糊逻辑温度控制器,并结合了炉温传感器和基于晶闸管的电灯泡驱动电路作为炉膛加热元件的接口链接。使用遗传算法离线使用隶属度函数的调整。成功演示了软硬件协同设计的模糊逻辑温度控制器的调试和执行。获得预期结果,以优化设定点温度。

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