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Temperature control by chip-implemented adaptive recurrent fuzzy controller designed by evolutionary algorithm

机译:进化算法设计的芯片实现自适应递归模糊控制器进行温度控制

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Online adaptive temperature control by field-programmable gate array (FPGA) - implemented adaptive recurrent fuzzy controller (ARFC) chip is proposed in this paper. The RFC is realized according to the structure of Takagi-Sugeno-Kang (TSK)-type recurrent fuzzy network. Direct inverse control configuration is used. To design RFC offline, evolutionary fuzzy controller using the hybrid of the Simplex method and particle swarm optimization (SPSO) is proposed. In SPSO, each RFC corresponds to a particle, and all the free parameters in RFC are optimally searched. We use the PSO to find a good solution globally, and the incorporation of the Simplex method helps find a better solution around the local region of the best solution found by PSO so far. Then, online adaptive temperature control with ARFC chip implemented by FPGA is proposed. In the ARFC chip, the consequent parameters of all rules are all tuned online using gradient descent. To verify the performance of the ARFC chip, experiments on a water bath temperature system are performed.
机译:本文提出了一种基于现场可编程门阵列(FPGA)的在线自适应温度控制-实现的自适应递归模糊控制器(ARFC)芯片。 RFC是根据Takagi-Sugeno-Kang(TSK)型递归模糊网络的结构实现的。使用直接逆控制配置。为了离线设计RFC,提出了基于单纯形法和粒子群算法(SPSO)的混合进化模糊控制器。在SPSO中,每个RFC都对应一个粒子,并且以最佳方式搜索RFC中的所有自由参数。我们使用PSO在全球范围内找到一个好的解决方案,而Simplex方法的并入有助于在到目前为止PSO找到的最佳解决方案的本地区域附近找到一个更好的解决方案。然后,提出了一种基于FPGA的ARFC在线自适应温度控制系统。在ARFC芯片中,所有规则的相应参数都使用梯度下降进行在线调整。为了验证ARFC芯片的性能,在水浴温度系统上进行了实验。

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