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首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part C. Journal of mechanical engineering science >Active control of surge in centrifugal compressors using a brain emotional learning-based intelligent controller
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Active control of surge in centrifugal compressors using a brain emotional learning-based intelligent controller

机译：使用基于大脑情感学习的智能控制器主动控制离心压缩机的喘振

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摘要

Efforts have been targeted at providing a comprehensive simulation of a centrifugal compressor undergoing surge. In the simulation process, an artificial neural network was utilized to produce an all-inclusive performance map encompassing those speeds not available in the provided curves. Two positive scenarios for the shaft speed, constant, and variable, were undertaken, and effects of load line on the dynamic response of the compressor have been studied. In order to achieve high-fidelity simulation in the variable speed case, an artificial neural network was utilized to produce an all-inclusive performance map encompassing those speeds not available in the provided curves. Moreover, effects of dynamic characteristics of throttle valve were also investigated. A novel controlling scheme, based on neuro-fuzzy control philosophy, was implemented to stabilize the compressor performance in the unstable region. Results indicate that if applied, this scheme could produce practical and satisfactory outcomes, possessing certain virtues compared to available techniques.
机译：努力的目标是提供对经历喘振的离心压缩机的全面模拟。在仿真过程中，使用了人工神经网络来生成包含所有速度的全包性能图，这些速度在提供的曲线中不可用。对轴速度进行了两个正向的假设，即恒定和可变，并且研究了负载线对压缩机动态响应的影响。为了在变速情况下实现高保真仿真，人工神经网络被用于生成涵盖所有性能的性能图，其中涵盖了所提供的曲线中没有的那些速度。此外，还研究了节气门动态特性的影响。实施了一种基于神经模糊控制原理的新颖控制方案，以稳定不稳定区域中的压缩机性能。结果表明，如果应用该方案，可以产生实用且令人满意的结果，与可用技术相比具有某些优点。

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