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Optimization of fuzzy controller of a wind power plant based on the swarm intelligence

机译:基于群体智能的风电厂模糊控制器优化

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The article considers the problem of the optimal control of a wind power plant based on fuzzy control and automation of generating the fuzzy rule base. Fuzzy rules by experts do not always provide a maximum power output of the wind plant and fuzzy rule bases require an adjustment in the case of changing the parameters of the wind power plant or the environment. This research proposes the method for optimizing the fuzzy rules base compiled by various experts. The method is based on balancing weights of fuzzy rules into the base by the Particle Swarm Optimization algorithm. The experiment has shown that the proposed method allows forming the fuzzy rule base as an exemplary optimal base from a non-optimized set of fuzzy rules. The optimal fuzzy rule base has been taken under consideration for the concrete control loop of wind power plant and the concrete fuzzy model of the wind.
机译:本文认为基于模糊控制和自动化产生模糊规则基础的风力电厂的最优控制问题。由专家的模糊规则并不总是提供风厂的最大功率输出,并且模糊规则基础需要调整风电厂或环境参数的情况。本研究提出了优化由各专家编制的模糊规则基础的方法。该方法基于粒子群优化算法将模糊规则的平衡重量平衡到基础。该实验表明,该方法允许将模糊规则基础形成为来自非优化的模糊规则集的示例性最优基础。风力发电厂混凝土控制回路和风的混凝土模糊模型,已经考虑了最佳模糊规则基础。

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