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基于MPSO-RBF预测控制的瓦斯监控系统研究

Research of Predictive Control Based on MPSO-RBF in Gas Supervision System

【作者】 赵丹

【导师】 付华;

【作者基本信息】 辽宁工程技术大学 , 控制理论与控制工程, 2009, 硕士

【摘要】 煤矿瓦斯突出是制约煤矿安全生产的主要因素,采掘工作面是瓦斯突出的多发地点,一旦发生将造成重大经济损失和人员伤亡。煤矿监控系统是保障煤矿安全生产的重要手段,而局部通风机和井下移动抽排泵是监控系统的主要监控设备。然而其现有的控制技术落后,很难满足采掘工作面连续通风和瓦斯安全排放的要求,因此,研究其控制技术具有重要的实际意义。本文结合瓦斯监控系统的特点,基于非线性模型预测控制的基本框架,首次提出了基于RBF预测模型和粒子群优化的煤矿瓦斯监控系统结构和算法。首先对该算法进行仿真研究,说明了RBF网络模型的泛化能力和粒子群优化的寻优速度和能力,并进行了可行性分析。最后将其应用于煤矿瓦斯监控系统,仿真结果显示此方法为降低瓦斯突出危险性提供了一个崭新的有效途径,结束了以往传统的控制瓦斯排放方式,减小了掘进工作面瓦斯事故发生率,具有较高的实用价值和广阔的应用前景。

【Abstract】 Gas outburst is considered as the main restrictive factor in coal mine production safety. In viewing of the fact that accident frequently happens in heading face, which could cause damage economic losses and casualties, the supervision system is served as an important measurement in guaranteeing the safety of mine production. Local fans and moving pump underground are the primary monitoring equipment in supervision system. However, the existing control technology is poor and hard to meet the requirements of heading face continuous ventilation and gas safety emission. Therefore, control technology studying has important practical significance.With consideration of the characteristics of the gas monitoring system and the basic framework based on nonlinear model predictive control, a new architecture and algorithm of the coal mine gas monitoring system is proposed in this paper. Prediction model based RBF and particle swarm optimization are adopted firstly in this theory. In order to demonstrate the generalization ability of RBF network model and the speed and capability optimization searching for particle swarm optimizing, a feasibility analysis is conducted and emulation test is processed. Thus, the verified theory is applied to coal mine gas monitoring system. Simulation results show that this method provides a new effective way to reduce the risk of gas outburst and puts an end to the traditional control of gas emissions from the previous way of reducing the accident rate of gas heading face. This method has a high practical value and broad application prospects in the coal mine gas monitoring system.

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