船舶动力系统智能控制

Intelligent control for marine power system

针对船舶动力系统存在着非线性、不确定性和复杂性,传统的速度调节系统已经不能满足控制需要,作者将模糊神经网络应用到复杂过程控制中去,实现动力系统的智能控制。采用模块建模法建立了汽轮机模型,给出了一种基于模糊神经网络的转速调节系统。并将粗糙集理论与模糊神经网络结合起来,利用粗糙集从观测数据中提取规则,并寻求最小规则集,解决了模糊神经网络'规则爆炸'问题。在MATLAB平台上进行仿真,结果表明该方法对于负荷的扰动及工况的变化有良好的控制效果。

Due the existence of nonlinearity, uncertainty and complexity in marine power system, conventional speed regulation system can no longer meet the controlling requirement. Fuzzy Neural Network was applied to the complex process modeling and logical inference to realize intelligent control of power system. Modular modeling methods are used to establish the model of steam turbine. A new type speed regulation system based on fuzzy neural network was presented. The method combines the rough set with fuzzy neural network, which can derive control rules from input output data effectively and find the minimal set of the rules. This method can solve the problem of ＂rule explosion＂. Results of simulation using Matlab indicate that the proposed method possesses the ability of good-quality control when the load disturbances and condition change.