双油箱液压系统的ANFIS数据驱动建模与实时模糊控制器试验

L. A. Torres-Salomao, J. Anzurez-Marín, J. M. Orozco-Sixtos, S. Ramirez-Zavala
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引用次数: 2

摘要

提出了一种基于数据驱动的非线性自适应网络模糊推理系统(ANFIS)的双油箱液压系统建模方法。本文还讨论了用遗传算法优化的1型模糊控制器的设计。利用所得到的ANFIS模型对控制器进行了仿真设计和测试,并用实际TTHS进行了实时验证。所获得的模型显示了对实际系统的准确和充分的描述,对于许多需要TTHS非线性功能表示的应用非常有用。所设计的控制器还显示了优异的性能,能够遵循各种形状的参考。这项工作成功地展示了软计算技术在实际工业复杂系统中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ANFIS data driven modeling and real-time Fuzzy Logic Controller test for a Two Tanks Hydraulic System
This paper presents a non-linear, data driven Adaptive Network based Fuzzy Inference System (ANFIS) modeling of a Two Tanks Hydraulic System (TTHS). The paper also addresses the design of a Type 1 Fuzzy Logic Controller optimized with Genetic Algorithms (GA). The controller was designed and tested in simulation with the obtained ANFIS model and validated in real-time with the actual TTHS. Obtained model shows an accurate and adequate description of the real system, useful for many applications that require a non-linear functioning representation of the TTHS. The designed controller also demonstrates excellent performance by being able to follow diverse shaped references. This work successfully demonstrates the utility of soft-computing techniques in their application to real world industrial complex systems.
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