在船舶蒸汽动力系统中,普遍采用锅炉增压形式对蒸汽动力进行最大化的利用,而锅炉增压系统中最重要的是控制器的设计,该控制系统的稳定性对整个锅炉系统的安全运行至关重要。本文从锅炉增压系统的基本工作原理出发,建立了一种船舶锅炉汽包水位的状态模型,对汽包的温度和水位状态进行全面描述,然后利用RBF神经网络算法建立了汽包状态的动态补偿模型,并设计了基于PID预测控制策略。仿真结果表明,本文提出的预测模型具有较好的鲁棒性和稳定性。
In the ship's steam power system, the boiler's supercharging form is used to maximize the steam power, and the most important controller in the boiler's supercharging system is designed. The stability of the control system to the whole boiler system of the safe operation is essential. Based on the basic working principle of the boiler booster system, a state model of boiler boiler drum water level is established, and the temperature and water level of the drum are described in detail. Then the RBF neural network algorithm is used to establish the drum state. The dynamic compensation model is designed, and the PID predictive control strategy is designed. The simulation results show that the proposed model has good robustness and stability.
2017,39(1A): 52-54 收稿日期:2016-10-18
DOI:10.3404/j.issn.1672-7619.2017.1A.018
分类号:U662
作者简介:王洋(1985-),男,硕士,讲师,研究方向为应用数学。
参考文献:
[1] 吴健, 赵德光, 张志杰. 基于神经网络的传感器动态补偿算法及DSP实现[J]. 计算机测量与控制, 2011(5):1239-1241, 1245.
[2] 唐令波, 雷玉勇, 邴龙健, 等. 基于模糊PID的工业锅炉汽包水位控制系统的仿真研究[J]. 机械设计与制造, 2009(11):110-112.
[3] 俞阿龙, 黄惟一. 基于改进遗传神经网络的微硅加速度传感器动态补偿研究[J]. 东南大学学报(自然科学版), 2004(4):455-458.
[4] MOHAMMADZADEH S, ZARGARI H, GHAYYEM M A. The application of intelligent computation (artificial neural network-ANN) prediction of sweet gas concentration in a gas absorption column[J]. Energy Sources Part A Recovery Utilization & Environmental Effects, 2015, 37(5):485-493.
[5] DAS K P, GANGULY S, CHATTOPADHYAY P P, et al. Exploring the possibilities of development of directly quenched TRIP-aided steel by the artificial neural networks (ANN) technique[J]. Advanced Manufacturing Processes, 2009, 24(1):68-77.
[6] SALMASI F, YıLDıRıM G, MASOODI A, et al. Predicting discharge coefficient of compound broad-crested weir by using genetic programming (GP) and artificial neural network (ANN) techniques[J]. Arabian Journal of Geosciences, 2013, 6(7):2709-2717.