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Identification of 2-DOF Pneumatic Artificial Muscle System with Multilayer Fuzzy Logic and Differential Evolution Algorithm

机译:具有多层模糊逻辑和差分演化算法的二进制气动人工肌肉系统的鉴定

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This paper proposes a new method for identifying a nonlinear pneumatic artificial muscle (PAM) 2-dof parallel system based on the novel NARX multilayer fuzzy model optimized by differential evolution (DE) algorithm. A multilayer fuzzy system is created by combining several MISO multilayer fuzzy models. Each MISO multilayer Fuzzy model is implemented through several Fuzzy Takagi-Sugeno sets. Then fuzzy structures and fuzzy rules of proposed multilayer fuzzy model were optimally trained by DE algorithm. The experiment results are presented. It proves a promisingly scalable and simple method to successfully identify nonlinear MIMO system.
机译:本文提出了一种新的方法,用于识别基于差分演进(DE)算法优化的新型NARX多层模糊模型的非线性气动人工肌肉(PAM)2-DOF系统。通过组合多个MISO多层模糊模型来创建多层模糊系统。每个MISO多层模糊模型通过几种模糊Takagi-Sugeno集实现。然后,所提出的多层模糊模型的模糊结构和模糊规则是由DE算法进行的最佳训练。提出了实验结果。它证明了一个有承诺的可扩展和简单的方法来成功识别非线性MIMO系统。

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