论文部分内容阅读
针对水轮机调节系统非线性、结构参数变化范围较大的特点，提出了一种能够在线学习的智能控制系统。它以模糊神经网络为学习器，以模糊推理和智能处理机构为控制器，将两者结合起来共同完成水轮发电机组的调节任务，并详细讨论了学习器的建立和学习方法及智能控制系统的运行方式。仿真研究表明，其有较强的学习能力、良好的实时控制性能，能适应水轮机调节系统结构、参数变化较大情况下的控制要求。
In view of the non-linearity of hydraulic turbine governing system and the wide range of structural parameters, an intelligent control system capable of online learning is proposed. It uses fuzzy neural network as learning device, fuzzy reasoning and intelligent processing mechanism as the controller, the two together to complete the task of regulating hydro-generating units, and discussed in detail the learning of the establishment and learning methods and intelligent control system The way of operation. Simulation studies show that it has strong learning ability, good real-time control performance, can adapt to the turbine control system structure, control parameters under large changes.