基于解耦模型的室内温湿度模糊控制

Q3 Engineering
S. Yordanova
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引用次数: 0

摘要

室内温度和湿度的控制对于确保最佳工作能力和有效休息所需的室内人体舒适度至关重要。为了满足高性能要求,植物非线性和变量耦合需要智能控制技术。本文提出了一种基于并行分布式补偿(PDC)原理的简单工业实现模糊逻辑控制器的设计方法,该控制器由线性局部解耦双变量控制器组成。它基于Takagi-Sugeno Kang(TSK)工厂模型,该模型使用专家知识和遗传算法的参数优化从实验获得的工厂阶跃响应中导出。该设计应用于实验室空调系统的温度和相对湿度控制。根据仿真估计,PDC系统优于现有的Mamdani双变量控制系统,具有更短的稳定时间、更高的鲁棒性和减少过冲的自适应特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decoupling Model-Based Fuzzy Logic Control of Room Temperature and Humidity
The control of room temperature and humidity is important for ensuring of the necessary indoor human comfort for optimal work capacity and effective rest. The plant nonlinearity and the variables coupling require intelligent control techniques in order to satisfy the high performance demands. The present paper suggests a procedure for the design of a simple for industrial implementation fuzzy logic controller on the principle of parallel distributed compensation (PDC) that consists of linear local decoupling two-variable controllers. It is based on a Takagi-Sugeno-Kang (TSK) plant model, derived from experimentally obtained plant step responses using expert knowledge and parameter optimisation via genetic algorithms. The design is applied for the control of the temperature and the relative humidity of a laboratory air-conditioning system. The PDC system outperforms an existing Mamdani two-variable control system with adaptive properties in shorter settling time, higher robustness and reduced overshoot, estimated from simulations.
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来源期刊
Advances in Systems Science and Applications
Advances in Systems Science and Applications Engineering-Engineering (all)
CiteScore
1.20
自引率
0.00%
发文量
0
期刊介绍: Advances in Systems Science and Applications (ASSA) is an international peer-reviewed open-source online academic journal. Its scope covers all major aspects of systems (and processes) analysis, modeling, simulation, and control, ranging from theoretical and methodological developments to a large variety of application areas. Survey articles and innovative results are also welcome. ASSA is aimed at the audience of scientists, engineers and researchers working in the framework of these problems. ASSA should be a platform on which researchers will be able to communicate and discuss both their specialized issues and interdisciplinary problems of systems analysis and its applications in science and industry, including data science, artificial intelligence, material science, manufacturing, transportation, power and energy, ecology, corporate management, public governance, finance, and many others.
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